4730 lines
146 KiB
Plaintext
4730 lines
146 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "HcpwFPAh51-R"
|
||
},
|
||
"source": [
|
||
"To run this, press \"*Runtime*\" and press \"*Run all*\" on a **free** Tesla T4 Google Colab instance!\n",
|
||
"<div class=\"align-center\">\n",
|
||
"<a href=\"https://unsloth.ai/\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png\" width=\"115\"></a>\n",
|
||
"<a href=\"https://discord.gg/unsloth\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/Discord button.png\" width=\"145\"></a>\n",
|
||
"<a href=\"https://docs.unsloth.ai/\"><img src=\"https://github.com/unslothai/unsloth/blob/main/images/documentation%20green%20button.png?raw=true\" width=\"125\"></a></a> Join Discord if you need help + ⭐ <i>Star us on <a href=\"https://github.com/unslothai/unsloth\">Github</a> </i> ⭐\n",
|
||
"</div>\n",
|
||
"\n",
|
||
"To install Unsloth on your own computer, follow the installation instructions on our Github page [here](https://docs.unsloth.ai/get-started/installing-+-updating).\n",
|
||
"\n",
|
||
"You will learn how to do [data prep](#Data), how to [train](#Train), how to [run the model](#Inference), & [how to save it](#Save)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "iM0HrYe551-S"
|
||
},
|
||
"source": [
|
||
"### News"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "YlBNJDGN51-S"
|
||
},
|
||
"source": [
|
||
"Unsloth now supports Text-to-Speech (TTS) models. Read our [guide here](https://docs.unsloth.ai/basics/text-to-speech-tts-fine-tuning).\n",
|
||
"\n",
|
||
"Read our **[Qwen3 Guide](https://docs.unsloth.ai/basics/qwen3-how-to-run-and-fine-tune)** and check out our new **[Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs)** quants which outperforms other quantization methods!\n",
|
||
"\n",
|
||
"Visit our docs for all our [model uploads](https://docs.unsloth.ai/get-started/all-our-models) and [notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks).\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "9JSHb-Ht51-S"
|
||
},
|
||
"source": [
|
||
"### Installation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "W-MEvzGu51-S"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"%%capture\n",
|
||
"import os\n",
|
||
"if \"COLAB_\" not in \"\".join(os.environ.keys()):\n",
|
||
" !pip install unsloth\n",
|
||
"else:\n",
|
||
" # Do this only in Colab notebooks! Otherwise use pip install unsloth\n",
|
||
" !pip install --no-deps bitsandbytes accelerate xformers==0.0.29.post3 peft trl triton cut_cross_entropy unsloth_zoo\n",
|
||
" !pip install sentencepiece protobuf \"datasets>=3.4.1\" huggingface_hub hf_transfer\n",
|
||
" !pip install --no-deps unsloth"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "QfXZVzCx51-S"
|
||
},
|
||
"source": [
|
||
"### Unsloth"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 300,
|
||
"referenced_widgets": [
|
||
"6e3c281f112b4a86af7a3ef95933d221",
|
||
"92395f250a154006923aaf9ea0a9c30b",
|
||
"f84bfc5390054ec687c157c4d68199a6",
|
||
"4228734651ca45e19fc7bda79817f9b3",
|
||
"4613edbbec6846edb5b1677c25d542b6",
|
||
"d032fe2ba5d647d99026fdade758c0cd",
|
||
"e9971d220fe24552a1e9aa299765cfb9",
|
||
"2be29a4553ad4dfea8a9bc620c81a3ae",
|
||
"94cbb87829d1486899e2ff6325c2ecdf",
|
||
"f878c2e00bc240c7b0333cce950080e1",
|
||
"6b908368de51428585552dfef6a83088",
|
||
"ac5eacaaee8346c080e54ea7a52648a4",
|
||
"7981edf408d54d41bbeac42da7492c6b",
|
||
"2b848e5a85bc42bc87945fd9ed5db038",
|
||
"e88c33f37d6849e0b1a6b41254104cb9",
|
||
"33843107b93647b28985bfc37ea781ca",
|
||
"76e5410e286a4a5abd6c213a38aa38bb",
|
||
"ae7e90a811f94e75997d6a9ed1be8596",
|
||
"bb9f3379310d4b04be694996f3137b28",
|
||
"75082ba15db445df907f5612976590ae",
|
||
"89934c4f26834f15b9889ec36fee3b65",
|
||
"e887160635cb4803b9f33845df615ec6",
|
||
"1c7bc5fdb7dd4c39af8d4c2c504ec3ed",
|
||
"843a27e619534ea8914f9d36386c364b",
|
||
"8f5adc70fbf248f2811527f620553be5",
|
||
"4ffb4b2f015046fb94c1115ed0397a20",
|
||
"5a232ed040f94633a2a374031284c1f6",
|
||
"2006be31c09349738e221295bb84939f",
|
||
"07055fc12b0841aaa5317f8252b5d347",
|
||
"1eb90e686e214122ae763b1b79ae321d",
|
||
"7a935956348e47c68fbdf05ddf4752f3",
|
||
"8653acb618ad4e76bbf1daa00ea71238",
|
||
"e3c3bd9c4c124b0a8c88c83c1fc747d3",
|
||
"1bd75ddaf57c4438a4e2c3070b9cef65",
|
||
"a3a3ef6d6337403cabea8b23f7c3021b",
|
||
"c2ea0a3f01f34ffa8c94ab9b5098e9da",
|
||
"68ea1d7cb8274a639b3fb5326f4218c3",
|
||
"39fef7b257614a0595f39355fa226b69",
|
||
"d125995cc0934239a01ba01b78529f21",
|
||
"634ae4c6cfe04673b1cdc9c9cac4cbf9",
|
||
"d7f92e8332374313bee87ccd427446a4",
|
||
"36799fbcd90d43128620ff98225a825d",
|
||
"5310346dd579424fa676b8e8e64790e7",
|
||
"0c1835f404db4846bb13b5da8d8f4447",
|
||
"29c5b713f07043dda51820523e5c8ff3",
|
||
"d7375f0f048841b29a20601c122666e8",
|
||
"f433ced9bfcd4a57ba691d3c1caeed08",
|
||
"da8ffc70820a48f5a12c6d4b5967015b",
|
||
"1a6db9aea6a64ae3aaef51d6265b35b2",
|
||
"331f516c7a76456d801bc2a2feb228aa",
|
||
"9be9074028da42d39d044a78393a861f",
|
||
"51cd9026b1664819a67712996ca97bd5",
|
||
"ea55293415ca48a4be97c2e1e4769122",
|
||
"8ea52b105a7e44978caca33c0e7e815b",
|
||
"3662f1445ef34a50b462e601ed31bb69"
|
||
]
|
||
},
|
||
"id": "QmUBVEnvCDJv",
|
||
"outputId": "0a47b925-663d-4543-9c61-994a6302f3c5"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n",
|
||
"==((====))== Unsloth 2024.8: Fast Llama patching. Transformers = 4.44.2.\n",
|
||
" \\\\ /| GPU: Tesla T4. Max memory: 14.748 GB. Platform = Linux.\n",
|
||
"O^O/ \\_/ \\ Pytorch: 2.4.0+cu121. CUDA = 7.5. CUDA Toolkit = 12.1.\n",
|
||
"\\ / Bfloat16 = FALSE. FA [Xformers = 0.0.27.post2. FA2 = False]\n",
|
||
" \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n",
|
||
"Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "6e3c281f112b4a86af7a3ef95933d221",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"model.safetensors: 0%| | 0.00/5.70G [00:00<?, ?B/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "ac5eacaaee8346c080e54ea7a52648a4",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"generation_config.json: 0%| | 0.00/230 [00:00<?, ?B/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "1c7bc5fdb7dd4c39af8d4c2c504ec3ed",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"tokenizer_config.json: 0%| | 0.00/50.6k [00:00<?, ?B/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "1bd75ddaf57c4438a4e2c3070b9cef65",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"tokenizer.json: 0%| | 0.00/9.09M [00:00<?, ?B/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "29c5b713f07043dda51820523e5c8ff3",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"special_tokens_map.json: 0%| | 0.00/345 [00:00<?, ?B/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from unsloth import FastLanguageModel\n",
|
||
"import torch\n",
|
||
"max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!\n",
|
||
"dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+\n",
|
||
"load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.\n",
|
||
"\n",
|
||
"# 4bit pre quantized models we support for 4x faster downloading + no OOMs.\n",
|
||
"fourbit_models = [\n",
|
||
" \"unsloth/Meta-Llama-3.1-8B-bnb-4bit\", # Llama-3.1 15 trillion tokens model 2x faster!\n",
|
||
" \"unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit\",\n",
|
||
" \"unsloth/Meta-Llama-3.1-70B-bnb-4bit\",\n",
|
||
" \"unsloth/Meta-Llama-3.1-405B-bnb-4bit\", # We also uploaded 4bit for 405b!\n",
|
||
" \"unsloth/Mistral-Nemo-Base-2407-bnb-4bit\", # New Mistral 12b 2x faster!\n",
|
||
" \"unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit\",\n",
|
||
" \"unsloth/mistral-7b-v0.3-bnb-4bit\", # Mistral v3 2x faster!\n",
|
||
" \"unsloth/mistral-7b-instruct-v0.3-bnb-4bit\",\n",
|
||
" \"unsloth/Phi-3.5-mini-instruct\", # Phi-3.5 2x faster!\n",
|
||
" \"unsloth/Phi-3-medium-4k-instruct\",\n",
|
||
" \"unsloth/gemma-2-9b-bnb-4bit\",\n",
|
||
" \"unsloth/gemma-2-27b-bnb-4bit\", # Gemma 2x faster!\n",
|
||
"] # More models at https://huggingface.co/unsloth\n",
|
||
"\n",
|
||
"model, tokenizer = FastLanguageModel.from_pretrained(\n",
|
||
" model_name = \"unsloth/Meta-Llama-3.1-8B\",\n",
|
||
" max_seq_length = max_seq_length,\n",
|
||
" dtype = dtype,\n",
|
||
" load_in_4bit = load_in_4bit,\n",
|
||
" # token = \"hf_...\", # use one if using gated models like meta-llama/Llama-2-7b-hf\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "SXd9bTZd1aaL"
|
||
},
|
||
"source": [
|
||
"We now add LoRA adapters so we only need to update 1 to 10% of all parameters!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "6bZsfBuZDeCL",
|
||
"outputId": "3e2a4618-6aa0-4f1c-d3a0-0ec45eb33237"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Unsloth 2024.8 patched 32 layers with 32 QKV layers, 32 O layers and 32 MLP layers.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"model = FastLanguageModel.get_peft_model(\n",
|
||
" model,\n",
|
||
" r = 16, # Choose any number > 0 ! Suggested 8, 16, 32, 64, 128\n",
|
||
" target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n",
|
||
" \"gate_proj\", \"up_proj\", \"down_proj\",],\n",
|
||
" lora_alpha = 16,\n",
|
||
" lora_dropout = 0, # Supports any, but = 0 is optimized\n",
|
||
" bias = \"none\", # Supports any, but = \"none\" is optimized\n",
|
||
" # [NEW] \"unsloth\" uses 30% less VRAM, fits 2x larger batch sizes!\n",
|
||
" use_gradient_checkpointing = \"unsloth\", # True or \"unsloth\" for very long context\n",
|
||
" random_state = 3407,\n",
|
||
" use_rslora = False, # We support rank stabilized LoRA\n",
|
||
" loftq_config = None, # And LoftQ\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "vITh0KVJ10qX"
|
||
},
|
||
"source": [
|
||
"<a name=\"Data\"></a>\n",
|
||
"### Data Prep\n",
|
||
"We now use the Alpaca dataset from [yahma](https://huggingface.co/datasets/yahma/alpaca-cleaned), which is a filtered version of 52K of the original [Alpaca dataset](https://crfm.stanford.edu/2023/03/13/alpaca.html). You can replace this code section with your own data prep.\n",
|
||
"\n",
|
||
"**[NOTE]** To train only on completions (ignoring the user's input) read TRL's docs [here](https://huggingface.co/docs/trl/sft_trainer#train-on-completions-only).\n",
|
||
"\n",
|
||
"**[NOTE]** Remember to add the **EOS_TOKEN** to the tokenized output!! Otherwise you'll get infinite generations!\n",
|
||
"\n",
|
||
"If you want to use the `llama-3` template for ShareGPT datasets, try our conversational [notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_(8B)-Alpaca.ipynb)\n",
|
||
"\n",
|
||
"For text completions like novel writing, try this [notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_(7B)-Text_Completion.ipynb)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 145,
|
||
"referenced_widgets": [
|
||
"5e8825fb770b41529f2129113cebc4a9",
|
||
"0a9dc233674e4096b7a988a5e4ebaf84",
|
||
"374fa9beda4042e1bf9a9b13de6e6674",
|
||
"e6533d3c91fd4359bc84ffd8e59af5a3",
|
||
"f9b01aebcbdc48a585b7942b0ee60a2d",
|
||
"d4b3770433bc41818372b7aed243fb31",
|
||
"19bcefcc1d874840ae9a9ca983e474b6",
|
||
"4011ce9370d74fad857ec8e1e99d314f",
|
||
"41f5fed060ad4c8d87b24602b720ef04",
|
||
"88fcd51819b5483c9ab22df7ef89ab64",
|
||
"e6ffac074f1b476ba2ade11b37732af3",
|
||
"98a6716e7438429ea322adb3e3264f91",
|
||
"68c686291b50430faeef0de7840e2c4b",
|
||
"953625aa1e824f8a8d203197b316b302",
|
||
"f899a815142542219bde22ff792fb60c",
|
||
"51ca174d26e94b5cb1e895aa3c770655",
|
||
"f4519637bb43400a80ce83505101e8a5",
|
||
"805676b197c94f5aa45956daa354640b",
|
||
"ce9fcc5eff1f460d80b703a4ca32dad1",
|
||
"3fef797403d14440afe599a3bf06b626",
|
||
"4e7cb8e988114ed4b6fe09ff9f682dff",
|
||
"a14bc1c2130842568a5fde6698731e5f",
|
||
"85cc6f24cba54563acb5598f54fed7b9",
|
||
"80a72037771e4da9be989eefabbc8e76",
|
||
"ba68b274c50b44ec9e02642378d271a6",
|
||
"f84d2fe4f1c24a34948755abf1f32b7f",
|
||
"86511967834f4484a5ec4af387b7d7a9",
|
||
"c97c40c2bf2a41a8ae1c75e0a9c8ebff",
|
||
"484e507f14424f2b9173595b985f4101",
|
||
"68a32b398e1c490393e01befdc260785",
|
||
"04cc963133d242779572d2e847fa3d65",
|
||
"94730f13e92a4c9aac35c2cfb21fc48c",
|
||
"620c0de28ec74f71a021a2be96dccf3a",
|
||
"6e1aff64771c402ab070f650562fa4c9",
|
||
"0078f897f2174217a307d95d4f9bd775",
|
||
"ecdeaab4f8c94d6dade63bb06857c969",
|
||
"735b85f0a0e9411cac4d704a504fcfc1",
|
||
"8e992e60416145a8b6eed744287ca0fb",
|
||
"8c195b5809604905b5e404baa30e8449",
|
||
"2247efac4283489bbd228330344388ab",
|
||
"e93d063faf984cc4aa51462418d9b57e",
|
||
"9d45b9a5de3e4cba9ac35ad2cb187f51",
|
||
"e99423a1ed3f4f72886b39368468b7c1",
|
||
"5f174718e5974a7cab024d113f662513"
|
||
]
|
||
},
|
||
"id": "LjY75GoYUCB8",
|
||
"outputId": "80d6c3b9-28c2-4ebf-9c57-6a0b77ce82b1"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "5e8825fb770b41529f2129113cebc4a9",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"Downloading readme: 0%| | 0.00/11.6k [00:00<?, ?B/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "98a6716e7438429ea322adb3e3264f91",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"Downloading data: 0%| | 0.00/44.3M [00:00<?, ?B/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "85cc6f24cba54563acb5598f54fed7b9",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"Generating train split: 0%| | 0/51760 [00:00<?, ? examples/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "6e1aff64771c402ab070f650562fa4c9",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"Map: 0%| | 0/51760 [00:00<?, ? examples/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"alpaca_prompt = \"\"\"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n",
|
||
"\n",
|
||
"### Instruction:\n",
|
||
"{}\n",
|
||
"\n",
|
||
"### Input:\n",
|
||
"{}\n",
|
||
"\n",
|
||
"### Response:\n",
|
||
"{}\"\"\"\n",
|
||
"\n",
|
||
"EOS_TOKEN = tokenizer.eos_token # Must add EOS_TOKEN\n",
|
||
"def formatting_prompts_func(examples):\n",
|
||
" instructions = examples[\"instruction\"]\n",
|
||
" inputs = examples[\"input\"]\n",
|
||
" outputs = examples[\"output\"]\n",
|
||
" texts = []\n",
|
||
" for instruction, input, output in zip(instructions, inputs, outputs):\n",
|
||
" # Must add EOS_TOKEN, otherwise your generation will go on forever!\n",
|
||
" text = alpaca_prompt.format(instruction, input, output) + EOS_TOKEN\n",
|
||
" texts.append(text)\n",
|
||
" return { \"text\" : texts, }\n",
|
||
"pass\n",
|
||
"\n",
|
||
"from datasets import load_dataset\n",
|
||
"dataset = load_dataset(\"yahma/alpaca-cleaned\", split = \"train\")\n",
|
||
"dataset = dataset.map(formatting_prompts_func, batched = True,)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "idAEIeSQ3xdS"
|
||
},
|
||
"source": [
|
||
"<a name=\"Train\"></a>\n",
|
||
"### Train the model\n",
|
||
"Now let's use Huggingface TRL's `SFTTrainer`! More docs here: [TRL SFT docs](https://huggingface.co/docs/trl/sft_trainer). We do 60 steps to speed things up, but you can set `num_train_epochs=1` for a full run, and turn off `max_steps=None`. We also support TRL's `DPOTrainer`!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 67,
|
||
"referenced_widgets": [
|
||
"3719bf6f9c6a4c6fbef93c5328c11a07",
|
||
"03f492b4b56f4d8e80e9395a65058b1b",
|
||
"39d9ef9fb35f47119f319f48eb222070",
|
||
"3d7cfb33ceaf417e851ac4393c65148b",
|
||
"ece66fa2f128456fa2a82b8a28d1211c",
|
||
"9695a640b0ff4e91af495bb59548e4b6",
|
||
"d4bd5559d4134d64a943d57972c6ef39",
|
||
"fbae6e599d1644f39e5d86efa0f9f997",
|
||
"00d425bca350451da6400f9f05c4a659",
|
||
"6a27d9ad4f064586a87636b10455d15b",
|
||
"77f4367616964a01a8c42416f5f4c147"
|
||
]
|
||
},
|
||
"id": "95_Nn-89DhsL",
|
||
"outputId": "29798478-b975-42d3-b32b-020a805cac35"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "3719bf6f9c6a4c6fbef93c5328c11a07",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"Map (num_proc=2): 0%| | 0/51760 [00:00<?, ? examples/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"max_steps is given, it will override any value given in num_train_epochs\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from trl import SFTTrainer\n",
|
||
"from transformers import TrainingArguments\n",
|
||
"from unsloth import is_bfloat16_supported\n",
|
||
"\n",
|
||
"trainer = SFTTrainer(\n",
|
||
" model = model,\n",
|
||
" tokenizer = tokenizer,\n",
|
||
" train_dataset = dataset,\n",
|
||
" dataset_text_field = \"text\",\n",
|
||
" max_seq_length = max_seq_length,\n",
|
||
" dataset_num_proc = 2,\n",
|
||
" packing = False, # Can make training 5x faster for short sequences.\n",
|
||
" args = TrainingArguments(\n",
|
||
" per_device_train_batch_size = 2,\n",
|
||
" gradient_accumulation_steps = 4,\n",
|
||
" warmup_steps = 5,\n",
|
||
" # num_train_epochs = 1, # Set this for 1 full training run.\n",
|
||
" max_steps = 60,\n",
|
||
" learning_rate = 2e-4,\n",
|
||
" fp16 = not is_bfloat16_supported(),\n",
|
||
" bf16 = is_bfloat16_supported(),\n",
|
||
" logging_steps = 1,\n",
|
||
" optim = \"adamw_8bit\",\n",
|
||
" weight_decay = 0.01,\n",
|
||
" lr_scheduler_type = \"linear\",\n",
|
||
" seed = 3407,\n",
|
||
" output_dir = \"outputs\",\n",
|
||
" report_to = \"none\", # Use this for WandB etc\n",
|
||
" ),\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"cellView": "form",
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "2ejIt2xSNKKp",
|
||
"outputId": "d397dd48-304c-4f42-ecbc-d5c9ce14989c"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"GPU = Tesla T4. Max memory = 14.748 GB.\n",
|
||
"5.984 GB of memory reserved.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# @title Show current memory stats\n",
|
||
"gpu_stats = torch.cuda.get_device_properties(0)\n",
|
||
"start_gpu_memory = round(torch.cuda.max_memory_reserved() / 1024 / 1024 / 1024, 3)\n",
|
||
"max_memory = round(gpu_stats.total_memory / 1024 / 1024 / 1024, 3)\n",
|
||
"print(f\"GPU = {gpu_stats.name}. Max memory = {max_memory} GB.\")\n",
|
||
"print(f\"{start_gpu_memory} GB of memory reserved.\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 1000
|
||
},
|
||
"id": "yqxqAZ7KJ4oL",
|
||
"outputId": "76534fb4-5f9a-4da4-9740-fcff4583fd1c"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"==((====))== Unsloth - 2x faster free finetuning | Num GPUs = 1\n",
|
||
" \\\\ /| Num examples = 51,760 | Num Epochs = 1\n",
|
||
"O^O/ \\_/ \\ Batch size per device = 2 | Gradient Accumulation steps = 4\n",
|
||
"\\ / Total batch size = 8 | Total steps = 60\n",
|
||
" \"-____-\" Number of trainable parameters = 41,943,040\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"\n",
|
||
" <div>\n",
|
||
" \n",
|
||
" <progress value='60' max='60' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
|
||
" [60/60 07:28, Epoch 0/1]\n",
|
||
" </div>\n",
|
||
" <table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: left;\">\n",
|
||
" <th>Step</th>\n",
|
||
" <th>Training Loss</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <td>1</td>\n",
|
||
" <td>1.817600</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>2</td>\n",
|
||
" <td>2.304200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>3</td>\n",
|
||
" <td>1.689300</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>4</td>\n",
|
||
" <td>1.938200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>5</td>\n",
|
||
" <td>1.656900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>6</td>\n",
|
||
" <td>1.621900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>7</td>\n",
|
||
" <td>1.187100</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>8</td>\n",
|
||
" <td>1.264200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>9</td>\n",
|
||
" <td>1.101200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>10</td>\n",
|
||
" <td>1.189500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>11</td>\n",
|
||
" <td>0.930800</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>12</td>\n",
|
||
" <td>0.959400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>13</td>\n",
|
||
" <td>0.929400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>14</td>\n",
|
||
" <td>1.048700</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>15</td>\n",
|
||
" <td>0.892800</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>16</td>\n",
|
||
" <td>0.901400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>17</td>\n",
|
||
" <td>1.009100</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>18</td>\n",
|
||
" <td>1.256100</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>19</td>\n",
|
||
" <td>1.016500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>20</td>\n",
|
||
" <td>0.882600</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>21</td>\n",
|
||
" <td>0.940500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>22</td>\n",
|
||
" <td>1.018500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>23</td>\n",
|
||
" <td>0.897200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>24</td>\n",
|
||
" <td>0.991900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>25</td>\n",
|
||
" <td>1.072000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>26</td>\n",
|
||
" <td>1.022900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>27</td>\n",
|
||
" <td>1.044900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>28</td>\n",
|
||
" <td>0.877800</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>29</td>\n",
|
||
" <td>0.843800</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>30</td>\n",
|
||
" <td>0.887500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>31</td>\n",
|
||
" <td>0.853400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>32</td>\n",
|
||
" <td>0.866000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>33</td>\n",
|
||
" <td>0.983200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>34</td>\n",
|
||
" <td>0.852200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>35</td>\n",
|
||
" <td>0.961200</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>36</td>\n",
|
||
" <td>0.856700</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>37</td>\n",
|
||
" <td>0.872300</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>38</td>\n",
|
||
" <td>0.751100</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>39</td>\n",
|
||
" <td>1.081400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>40</td>\n",
|
||
" <td>1.174400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>41</td>\n",
|
||
" <td>0.893400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>42</td>\n",
|
||
" <td>0.977500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>43</td>\n",
|
||
" <td>0.957100</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>44</td>\n",
|
||
" <td>0.908100</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>45</td>\n",
|
||
" <td>0.915000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>46</td>\n",
|
||
" <td>0.973400</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>47</td>\n",
|
||
" <td>0.870900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>48</td>\n",
|
||
" <td>1.196500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>49</td>\n",
|
||
" <td>0.907500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>50</td>\n",
|
||
" <td>1.031300</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>51</td>\n",
|
||
" <td>1.015900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>52</td>\n",
|
||
" <td>0.907900</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>53</td>\n",
|
||
" <td>0.977000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>54</td>\n",
|
||
" <td>1.154300</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>55</td>\n",
|
||
" <td>0.778000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>56</td>\n",
|
||
" <td>1.013300</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>57</td>\n",
|
||
" <td>0.886800</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>58</td>\n",
|
||
" <td>0.827500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>59</td>\n",
|
||
" <td>0.852300</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>60</td>\n",
|
||
" <td>0.896600</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table><p>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"trainer_stats = trainer.train()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"cellView": "form",
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "pCqnaKmlO1U9",
|
||
"outputId": "edf33a96-b12c-4bba-9771-59e18aee707c"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"462.7198 seconds used for training.\n",
|
||
"7.71 minutes used for training.\n",
|
||
"Peak reserved memory = 7.922 GB.\n",
|
||
"Peak reserved memory for training = 1.938 GB.\n",
|
||
"Peak reserved memory % of max memory = 53.716 %.\n",
|
||
"Peak reserved memory for training % of max memory = 13.141 %.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# @title Show final memory and time stats\n",
|
||
"used_memory = round(torch.cuda.max_memory_reserved() / 1024 / 1024 / 1024, 3)\n",
|
||
"used_memory_for_lora = round(used_memory - start_gpu_memory, 3)\n",
|
||
"used_percentage = round(used_memory / max_memory * 100, 3)\n",
|
||
"lora_percentage = round(used_memory_for_lora / max_memory * 100, 3)\n",
|
||
"print(f\"{trainer_stats.metrics['train_runtime']} seconds used for training.\")\n",
|
||
"print(\n",
|
||
" f\"{round(trainer_stats.metrics['train_runtime']/60, 2)} minutes used for training.\"\n",
|
||
")\n",
|
||
"print(f\"Peak reserved memory = {used_memory} GB.\")\n",
|
||
"print(f\"Peak reserved memory for training = {used_memory_for_lora} GB.\")\n",
|
||
"print(f\"Peak reserved memory % of max memory = {used_percentage} %.\")\n",
|
||
"print(f\"Peak reserved memory for training % of max memory = {lora_percentage} %.\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "ekOmTR1hSNcr"
|
||
},
|
||
"source": [
|
||
"<a name=\"Inference\"></a>\n",
|
||
"### Inference\n",
|
||
"Let's run the model! You can change the instruction and input - leave the output blank!\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "kR3gIAX-SM2q",
|
||
"outputId": "087c5c13-e946-4c35-e4f2-e07a88f9ac32"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"['<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\\n\\n### Instruction:\\nContinue the fibonnaci sequence.\\n\\n### Input:\\n1, 1, 2, 3, 5, 8\\n\\n### Response:\\n13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025']"
|
||
]
|
||
},
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# alpaca_prompt = Copied from above\n",
|
||
"FastLanguageModel.for_inference(model) # Enable native 2x faster inference\n",
|
||
"inputs = tokenizer(\n",
|
||
"[\n",
|
||
" alpaca_prompt.format(\n",
|
||
" \"Continue the fibonnaci sequence.\", # instruction\n",
|
||
" \"1, 1, 2, 3, 5, 8\", # input\n",
|
||
" \"\", # output - leave this blank for generation!\n",
|
||
" )\n",
|
||
"], return_tensors = \"pt\").to(\"cuda\")\n",
|
||
"\n",
|
||
"outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)\n",
|
||
"tokenizer.batch_decode(outputs)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "CrSvZObor0lY"
|
||
},
|
||
"source": [
|
||
" You can also use a `TextStreamer` for continuous inference - so you can see the generation token by token, instead of waiting the whole time!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "e2pEuRb1r2Vg",
|
||
"outputId": "b13f5e53-4ca4-4551-dffa-aaa3c514dca4"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n",
|
||
"\n",
|
||
"### Instruction:\n",
|
||
"Continue the fibonnaci sequence.\n",
|
||
"\n",
|
||
"### Input:\n",
|
||
"1, 1, 2, 3, 5, 8\n",
|
||
"\n",
|
||
"### Response:\n",
|
||
"13, 21, 34, 55, 89, 144<|end_of_text|>\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# alpaca_prompt = Copied from above\n",
|
||
"FastLanguageModel.for_inference(model) # Enable native 2x faster inference\n",
|
||
"inputs = tokenizer(\n",
|
||
"[\n",
|
||
" alpaca_prompt.format(\n",
|
||
" \"Continue the fibonnaci sequence.\", # instruction\n",
|
||
" \"1, 1, 2, 3, 5, 8\", # input\n",
|
||
" \"\", # output - leave this blank for generation!\n",
|
||
" )\n",
|
||
"], return_tensors = \"pt\").to(\"cuda\")\n",
|
||
"\n",
|
||
"from transformers import TextStreamer\n",
|
||
"text_streamer = TextStreamer(tokenizer)\n",
|
||
"_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 128)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "uMuVrWbjAzhc"
|
||
},
|
||
"source": [
|
||
"<a name=\"Save\"></a>\n",
|
||
"### Saving, loading finetuned models\n",
|
||
"To save the final model as LoRA adapters, either use Huggingface's `push_to_hub` for an online save or `save_pretrained` for a local save.\n",
|
||
"\n",
|
||
"**[NOTE]** This ONLY saves the LoRA adapters, and not the full model. To save to 16bit or GGUF, scroll down!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "upcOlWe7A1vc",
|
||
"outputId": "030a6e13-9371-4717-c5c5-d4e3563e0cca"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"('lora_model/tokenizer_config.json',\n",
|
||
" 'lora_model/special_tokens_map.json',\n",
|
||
" 'lora_model/tokenizer.json')"
|
||
]
|
||
},
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"model.save_pretrained(\"lora_model\") # Local saving\n",
|
||
"tokenizer.save_pretrained(\"lora_model\")\n",
|
||
"# model.push_to_hub(\"your_name/lora_model\", token = \"...\") # Online saving\n",
|
||
"# tokenizer.push_to_hub(\"your_name/lora_model\", token = \"...\") # Online saving"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "AEEcJ4qfC7Lp"
|
||
},
|
||
"source": [
|
||
"Now if you want to load the LoRA adapters we just saved for inference, set `False` to `True`:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "MKX_XKs_BNZR",
|
||
"outputId": "f8e7d3fe-8e4d-49ee-944f-08e70cdc1d87"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n",
|
||
"\n",
|
||
"### Instruction:\n",
|
||
"What is a famous tall tower in Paris?\n",
|
||
"\n",
|
||
"### Input:\n",
|
||
"\n",
|
||
"\n",
|
||
"### Response:\n",
|
||
"One of the most famous and iconic tall towers in Paris is the Eiffel Tower. Standing at 324 meters (1,063 feet) tall, this wrought iron tower is a symbol of the city and a must-see attraction for tourists from all over the world.<|end_of_text|>\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"if False:\n",
|
||
" from unsloth import FastLanguageModel\n",
|
||
" model, tokenizer = FastLanguageModel.from_pretrained(\n",
|
||
" model_name = \"lora_model\", # YOUR MODEL YOU USED FOR TRAINING\n",
|
||
" max_seq_length = max_seq_length,\n",
|
||
" dtype = dtype,\n",
|
||
" load_in_4bit = load_in_4bit,\n",
|
||
" )\n",
|
||
" FastLanguageModel.for_inference(model) # Enable native 2x faster inference\n",
|
||
"\n",
|
||
"# alpaca_prompt = You MUST copy from above!\n",
|
||
"\n",
|
||
"inputs = tokenizer(\n",
|
||
"[\n",
|
||
" alpaca_prompt.format(\n",
|
||
" \"What is a famous tall tower in Paris?\", # instruction\n",
|
||
" \"\", # input\n",
|
||
" \"\", # output - leave this blank for generation!\n",
|
||
" )\n",
|
||
"], return_tensors = \"pt\").to(\"cuda\")\n",
|
||
"\n",
|
||
"from transformers import TextStreamer\n",
|
||
"text_streamer = TextStreamer(tokenizer)\n",
|
||
"_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 128)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "QQMjaNrjsU5_"
|
||
},
|
||
"source": [
|
||
"You can also use Hugging Face's `AutoModelForPeftCausalLM`. Only use this if you do not have `unsloth` installed. It can be hopelessly slow, since `4bit` model downloading is not supported, and Unsloth's **inference is 2x faster**."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "yFfaXG0WsQuE"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"if False:\n",
|
||
" # I highly do NOT suggest - use Unsloth if possible\n",
|
||
" from peft import AutoPeftModelForCausalLM\n",
|
||
" from transformers import AutoTokenizer\n",
|
||
" model = AutoPeftModelForCausalLM.from_pretrained(\n",
|
||
" \"lora_model\", # YOUR MODEL YOU USED FOR TRAINING\n",
|
||
" load_in_4bit = load_in_4bit,\n",
|
||
" )\n",
|
||
" tokenizer = AutoTokenizer.from_pretrained(\"lora_model\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "f422JgM9sdVT"
|
||
},
|
||
"source": [
|
||
"### Saving to float16 for VLLM\n",
|
||
"\n",
|
||
"We also support saving to `float16` directly. Select `merged_16bit` for float16 or `merged_4bit` for int4. We also allow `lora` adapters as a fallback. Use `push_to_hub_merged` to upload to your Hugging Face account! You can go to https://huggingface.co/settings/tokens for your personal tokens."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "iHjt_SMYsd3P"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Merge to 16bit\n",
|
||
"if False: model.save_pretrained_merged(\"model\", tokenizer, save_method = \"merged_16bit\",)\n",
|
||
"if False: model.push_to_hub_merged(\"hf/model\", tokenizer, save_method = \"merged_16bit\", token = \"\")\n",
|
||
"\n",
|
||
"# Merge to 4bit\n",
|
||
"if False: model.save_pretrained_merged(\"model\", tokenizer, save_method = \"merged_4bit\",)\n",
|
||
"if False: model.push_to_hub_merged(\"hf/model\", tokenizer, save_method = \"merged_4bit\", token = \"\")\n",
|
||
"\n",
|
||
"# Just LoRA adapters\n",
|
||
"if False:\n",
|
||
" model.save_pretrained(\"model\")\n",
|
||
" tokenizer.save_pretrained(\"model\")\n",
|
||
"if False:\n",
|
||
" model.push_to_hub(\"hf/model\", token = \"\")\n",
|
||
" tokenizer.push_to_hub(\"hf/model\", token = \"\")\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "TCv4vXHd61i7"
|
||
},
|
||
"source": [
|
||
"### GGUF / llama.cpp Conversion\n",
|
||
"To save to `GGUF` / `llama.cpp`, we support it natively now! We clone `llama.cpp` and we default save it to `q8_0`. We allow all methods like `q4_k_m`. Use `save_pretrained_gguf` for local saving and `push_to_hub_gguf` for uploading to HF.\n",
|
||
"\n",
|
||
"Some supported quant methods (full list on our [Wiki page](https://github.com/unslothai/unsloth/wiki#gguf-quantization-options)):\n",
|
||
"* `q8_0` - Fast conversion. High resource use, but generally acceptable.\n",
|
||
"* `q4_k_m` - Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K.\n",
|
||
"* `q5_k_m` - Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K.\n",
|
||
"\n",
|
||
"[**NEW**] To finetune and auto export to Ollama, try our [Ollama notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_(8B)-Ollama.ipynb)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "FqfebeAdT073"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Save to 8bit Q8_0\n",
|
||
"if False: model.save_pretrained_gguf(\"model\", tokenizer,)\n",
|
||
"# Remember to go to https://huggingface.co/settings/tokens for a token!\n",
|
||
"# And change hf to your username!\n",
|
||
"if False: model.push_to_hub_gguf(\"hf/model\", tokenizer, token = \"\")\n",
|
||
"\n",
|
||
"# Save to 16bit GGUF\n",
|
||
"if False: model.save_pretrained_gguf(\"model\", tokenizer, quantization_method = \"f16\")\n",
|
||
"if False: model.push_to_hub_gguf(\"hf/model\", tokenizer, quantization_method = \"f16\", token = \"\")\n",
|
||
"\n",
|
||
"# Save to q4_k_m GGUF\n",
|
||
"if False: model.save_pretrained_gguf(\"model\", tokenizer, quantization_method = \"q4_k_m\")\n",
|
||
"if False: model.push_to_hub_gguf(\"hf/model\", tokenizer, quantization_method = \"q4_k_m\", token = \"\")\n",
|
||
"\n",
|
||
"# Save to multiple GGUF options - much faster if you want multiple!\n",
|
||
"if False:\n",
|
||
" model.push_to_hub_gguf(\n",
|
||
" \"hf/model\", # Change hf to your username!\n",
|
||
" tokenizer,\n",
|
||
" quantization_method = [\"q4_k_m\", \"q8_0\", \"q5_k_m\",],\n",
|
||
" token = \"\",\n",
|
||
" )"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "3DRvrmz051-X"
|
||
},
|
||
"source": [
|
||
"Now, use the `model-unsloth.gguf` file or `model-unsloth-Q4_K_M.gguf` file in llama.cpp or a UI based system like Jan or Open WebUI. You can install Jan [here](https://github.com/janhq/jan) and Open WebUI [here](https://github.com/open-webui/open-webui)\n",
|
||
"\n",
|
||
"And we're done! If you have any questions on Unsloth, we have a [Discord](https://discord.gg/unsloth) channel! If you find any bugs or want to keep updated with the latest LLM stuff, or need help, join projects etc, feel free to join our Discord!\n",
|
||
"\n",
|
||
"Some other links:\n",
|
||
"1. Train your own reasoning model - Llama GRPO notebook [Free Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-GRPO.ipynb)\n",
|
||
"2. Saving finetunes to Ollama. [Free notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_(8B)-Ollama.ipynb)\n",
|
||
"3. Llama 3.2 Vision finetuning - Radiography use case. [Free Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_(11B)-Vision.ipynb)\n",
|
||
"6. See notebooks for DPO, ORPO, Continued pretraining, conversational finetuning and more on our [documentation](https://docs.unsloth.ai/get-started/unsloth-notebooks)!\n",
|
||
"\n",
|
||
"<div class=\"align-center\">\n",
|
||
" <a href=\"https://unsloth.ai\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png\" width=\"115\"></a>\n",
|
||
" <a href=\"https://discord.gg/unsloth\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/Discord.png\" width=\"145\"></a>\n",
|
||
" <a href=\"https://docs.unsloth.ai/\"><img src=\"https://github.com/unslothai/unsloth/blob/main/images/documentation%20green%20button.png?raw=true\" width=\"125\"></a>\n",
|
||
"\n",
|
||
" Join Discord if you need help + ⭐️ <i>Star us on <a href=\"https://github.com/unslothai/unsloth\">Github</a> </i> ⭐️\n",
|
||
"</div>\n"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"accelerator": "GPU",
|
||
"colab": {
|
||
"gpuType": "T4",
|
||
"provenance": [
|
||
{
|
||
"file_id": "https://github.com/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-Alpaca.ipynb",
|
||
"timestamp": 1750013020648
|
||
}
|
||
]
|
||
},
|
||
"kernelspec": {
|
||
"display_name": "finetune",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"name": "python",
|
||
"version": "3.10.18"
|
||
},
|
||
"widgets": {
|
||
"application/vnd.jupyter.widget-state+json": {
|
||
"0078f897f2174217a307d95d4f9bd775": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_8c195b5809604905b5e404baa30e8449",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_2247efac4283489bbd228330344388ab",
|
||
"value": "Map: 100%"
|
||
}
|
||
},
|
||
"00d425bca350451da6400f9f05c4a659": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"03f492b4b56f4d8e80e9395a65058b1b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_9695a640b0ff4e91af495bb59548e4b6",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_d4bd5559d4134d64a943d57972c6ef39",
|
||
"value": "Map (num_proc=2): 100%"
|
||
}
|
||
},
|
||
"04cc963133d242779572d2e847fa3d65": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"07055fc12b0841aaa5317f8252b5d347": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"0a9dc233674e4096b7a988a5e4ebaf84": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_d4b3770433bc41818372b7aed243fb31",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_19bcefcc1d874840ae9a9ca983e474b6",
|
||
"value": "Downloading readme: 100%"
|
||
}
|
||
},
|
||
"0c1835f404db4846bb13b5da8d8f4447": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"19bcefcc1d874840ae9a9ca983e474b6": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"1a6db9aea6a64ae3aaef51d6265b35b2": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"1bd75ddaf57c4438a4e2c3070b9cef65": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_a3a3ef6d6337403cabea8b23f7c3021b",
|
||
"IPY_MODEL_c2ea0a3f01f34ffa8c94ab9b5098e9da",
|
||
"IPY_MODEL_68ea1d7cb8274a639b3fb5326f4218c3"
|
||
],
|
||
"layout": "IPY_MODEL_39fef7b257614a0595f39355fa226b69"
|
||
}
|
||
},
|
||
"1c7bc5fdb7dd4c39af8d4c2c504ec3ed": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_843a27e619534ea8914f9d36386c364b",
|
||
"IPY_MODEL_8f5adc70fbf248f2811527f620553be5",
|
||
"IPY_MODEL_4ffb4b2f015046fb94c1115ed0397a20"
|
||
],
|
||
"layout": "IPY_MODEL_5a232ed040f94633a2a374031284c1f6"
|
||
}
|
||
},
|
||
"1eb90e686e214122ae763b1b79ae321d": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"2006be31c09349738e221295bb84939f": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"2247efac4283489bbd228330344388ab": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"29c5b713f07043dda51820523e5c8ff3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_d7375f0f048841b29a20601c122666e8",
|
||
"IPY_MODEL_f433ced9bfcd4a57ba691d3c1caeed08",
|
||
"IPY_MODEL_da8ffc70820a48f5a12c6d4b5967015b"
|
||
],
|
||
"layout": "IPY_MODEL_1a6db9aea6a64ae3aaef51d6265b35b2"
|
||
}
|
||
},
|
||
"2b848e5a85bc42bc87945fd9ed5db038": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_bb9f3379310d4b04be694996f3137b28",
|
||
"max": 230,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_75082ba15db445df907f5612976590ae",
|
||
"value": 230
|
||
}
|
||
},
|
||
"2be29a4553ad4dfea8a9bc620c81a3ae": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"331f516c7a76456d801bc2a2feb228aa": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"33843107b93647b28985bfc37ea781ca": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"3662f1445ef34a50b462e601ed31bb69": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"36799fbcd90d43128620ff98225a825d": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"3719bf6f9c6a4c6fbef93c5328c11a07": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_03f492b4b56f4d8e80e9395a65058b1b",
|
||
"IPY_MODEL_39d9ef9fb35f47119f319f48eb222070",
|
||
"IPY_MODEL_3d7cfb33ceaf417e851ac4393c65148b"
|
||
],
|
||
"layout": "IPY_MODEL_ece66fa2f128456fa2a82b8a28d1211c"
|
||
}
|
||
},
|
||
"374fa9beda4042e1bf9a9b13de6e6674": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_4011ce9370d74fad857ec8e1e99d314f",
|
||
"max": 11610,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_41f5fed060ad4c8d87b24602b720ef04",
|
||
"value": 11610
|
||
}
|
||
},
|
||
"39d9ef9fb35f47119f319f48eb222070": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_fbae6e599d1644f39e5d86efa0f9f997",
|
||
"max": 51760,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_00d425bca350451da6400f9f05c4a659",
|
||
"value": 51760
|
||
}
|
||
},
|
||
"39fef7b257614a0595f39355fa226b69": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"3d7cfb33ceaf417e851ac4393c65148b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_6a27d9ad4f064586a87636b10455d15b",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_77f4367616964a01a8c42416f5f4c147",
|
||
"value": " 51760/51760 [00:50<00:00, 1965.57 examples/s]"
|
||
}
|
||
},
|
||
"3fef797403d14440afe599a3bf06b626": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"4011ce9370d74fad857ec8e1e99d314f": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"41f5fed060ad4c8d87b24602b720ef04": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"4228734651ca45e19fc7bda79817f9b3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_f878c2e00bc240c7b0333cce950080e1",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_6b908368de51428585552dfef6a83088",
|
||
"value": " 5.70G/5.70G [00:45<00:00, 645MB/s]"
|
||
}
|
||
},
|
||
"4613edbbec6846edb5b1677c25d542b6": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"484e507f14424f2b9173595b985f4101": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"4e7cb8e988114ed4b6fe09ff9f682dff": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"4ffb4b2f015046fb94c1115ed0397a20": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_8653acb618ad4e76bbf1daa00ea71238",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_e3c3bd9c4c124b0a8c88c83c1fc747d3",
|
||
"value": " 50.6k/50.6k [00:00<00:00, 2.29MB/s]"
|
||
}
|
||
},
|
||
"51ca174d26e94b5cb1e895aa3c770655": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"51cd9026b1664819a67712996ca97bd5": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"5310346dd579424fa676b8e8e64790e7": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"5a232ed040f94633a2a374031284c1f6": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"5e8825fb770b41529f2129113cebc4a9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_0a9dc233674e4096b7a988a5e4ebaf84",
|
||
"IPY_MODEL_374fa9beda4042e1bf9a9b13de6e6674",
|
||
"IPY_MODEL_e6533d3c91fd4359bc84ffd8e59af5a3"
|
||
],
|
||
"layout": "IPY_MODEL_f9b01aebcbdc48a585b7942b0ee60a2d"
|
||
}
|
||
},
|
||
"5f174718e5974a7cab024d113f662513": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"620c0de28ec74f71a021a2be96dccf3a": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"634ae4c6cfe04673b1cdc9c9cac4cbf9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"68a32b398e1c490393e01befdc260785": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"68c686291b50430faeef0de7840e2c4b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_f4519637bb43400a80ce83505101e8a5",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_805676b197c94f5aa45956daa354640b",
|
||
"value": "Downloading data: 100%"
|
||
}
|
||
},
|
||
"68ea1d7cb8274a639b3fb5326f4218c3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_5310346dd579424fa676b8e8e64790e7",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_0c1835f404db4846bb13b5da8d8f4447",
|
||
"value": " 9.09M/9.09M [00:00<00:00, 17.1MB/s]"
|
||
}
|
||
},
|
||
"6a27d9ad4f064586a87636b10455d15b": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"6b908368de51428585552dfef6a83088": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"6e1aff64771c402ab070f650562fa4c9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_0078f897f2174217a307d95d4f9bd775",
|
||
"IPY_MODEL_ecdeaab4f8c94d6dade63bb06857c969",
|
||
"IPY_MODEL_735b85f0a0e9411cac4d704a504fcfc1"
|
||
],
|
||
"layout": "IPY_MODEL_8e992e60416145a8b6eed744287ca0fb"
|
||
}
|
||
},
|
||
"6e3c281f112b4a86af7a3ef95933d221": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_92395f250a154006923aaf9ea0a9c30b",
|
||
"IPY_MODEL_f84bfc5390054ec687c157c4d68199a6",
|
||
"IPY_MODEL_4228734651ca45e19fc7bda79817f9b3"
|
||
],
|
||
"layout": "IPY_MODEL_4613edbbec6846edb5b1677c25d542b6"
|
||
}
|
||
},
|
||
"735b85f0a0e9411cac4d704a504fcfc1": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_e99423a1ed3f4f72886b39368468b7c1",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_5f174718e5974a7cab024d113f662513",
|
||
"value": " 51760/51760 [00:00<00:00, 52999.05 examples/s]"
|
||
}
|
||
},
|
||
"75082ba15db445df907f5612976590ae": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"76e5410e286a4a5abd6c213a38aa38bb": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"77f4367616964a01a8c42416f5f4c147": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"7981edf408d54d41bbeac42da7492c6b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_76e5410e286a4a5abd6c213a38aa38bb",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_ae7e90a811f94e75997d6a9ed1be8596",
|
||
"value": "generation_config.json: 100%"
|
||
}
|
||
},
|
||
"7a935956348e47c68fbdf05ddf4752f3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"805676b197c94f5aa45956daa354640b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"80a72037771e4da9be989eefabbc8e76": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_c97c40c2bf2a41a8ae1c75e0a9c8ebff",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_484e507f14424f2b9173595b985f4101",
|
||
"value": "Generating train split: 100%"
|
||
}
|
||
},
|
||
"843a27e619534ea8914f9d36386c364b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_2006be31c09349738e221295bb84939f",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_07055fc12b0841aaa5317f8252b5d347",
|
||
"value": "tokenizer_config.json: 100%"
|
||
}
|
||
},
|
||
"85cc6f24cba54563acb5598f54fed7b9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_80a72037771e4da9be989eefabbc8e76",
|
||
"IPY_MODEL_ba68b274c50b44ec9e02642378d271a6",
|
||
"IPY_MODEL_f84d2fe4f1c24a34948755abf1f32b7f"
|
||
],
|
||
"layout": "IPY_MODEL_86511967834f4484a5ec4af387b7d7a9"
|
||
}
|
||
},
|
||
"86511967834f4484a5ec4af387b7d7a9": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"8653acb618ad4e76bbf1daa00ea71238": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"88fcd51819b5483c9ab22df7ef89ab64": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"89934c4f26834f15b9889ec36fee3b65": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"8c195b5809604905b5e404baa30e8449": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"8e992e60416145a8b6eed744287ca0fb": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"8ea52b105a7e44978caca33c0e7e815b": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"8f5adc70fbf248f2811527f620553be5": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_1eb90e686e214122ae763b1b79ae321d",
|
||
"max": 50570,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_7a935956348e47c68fbdf05ddf4752f3",
|
||
"value": 50570
|
||
}
|
||
},
|
||
"92395f250a154006923aaf9ea0a9c30b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_d032fe2ba5d647d99026fdade758c0cd",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_e9971d220fe24552a1e9aa299765cfb9",
|
||
"value": "model.safetensors: 100%"
|
||
}
|
||
},
|
||
"94730f13e92a4c9aac35c2cfb21fc48c": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"94cbb87829d1486899e2ff6325c2ecdf": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"953625aa1e824f8a8d203197b316b302": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_ce9fcc5eff1f460d80b703a4ca32dad1",
|
||
"max": 44307561,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_3fef797403d14440afe599a3bf06b626",
|
||
"value": 44307561
|
||
}
|
||
},
|
||
"9695a640b0ff4e91af495bb59548e4b6": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"98a6716e7438429ea322adb3e3264f91": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_68c686291b50430faeef0de7840e2c4b",
|
||
"IPY_MODEL_953625aa1e824f8a8d203197b316b302",
|
||
"IPY_MODEL_f899a815142542219bde22ff792fb60c"
|
||
],
|
||
"layout": "IPY_MODEL_51ca174d26e94b5cb1e895aa3c770655"
|
||
}
|
||
},
|
||
"9be9074028da42d39d044a78393a861f": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"9d45b9a5de3e4cba9ac35ad2cb187f51": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"a14bc1c2130842568a5fde6698731e5f": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"a3a3ef6d6337403cabea8b23f7c3021b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_d125995cc0934239a01ba01b78529f21",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_634ae4c6cfe04673b1cdc9c9cac4cbf9",
|
||
"value": "tokenizer.json: 100%"
|
||
}
|
||
},
|
||
"ac5eacaaee8346c080e54ea7a52648a4": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_7981edf408d54d41bbeac42da7492c6b",
|
||
"IPY_MODEL_2b848e5a85bc42bc87945fd9ed5db038",
|
||
"IPY_MODEL_e88c33f37d6849e0b1a6b41254104cb9"
|
||
],
|
||
"layout": "IPY_MODEL_33843107b93647b28985bfc37ea781ca"
|
||
}
|
||
},
|
||
"ae7e90a811f94e75997d6a9ed1be8596": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"ba68b274c50b44ec9e02642378d271a6": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_68a32b398e1c490393e01befdc260785",
|
||
"max": 51760,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_04cc963133d242779572d2e847fa3d65",
|
||
"value": 51760
|
||
}
|
||
},
|
||
"bb9f3379310d4b04be694996f3137b28": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"c2ea0a3f01f34ffa8c94ab9b5098e9da": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_d7f92e8332374313bee87ccd427446a4",
|
||
"max": 9085657,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_36799fbcd90d43128620ff98225a825d",
|
||
"value": 9085657
|
||
}
|
||
},
|
||
"c97c40c2bf2a41a8ae1c75e0a9c8ebff": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"ce9fcc5eff1f460d80b703a4ca32dad1": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d032fe2ba5d647d99026fdade758c0cd": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d125995cc0934239a01ba01b78529f21": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d4b3770433bc41818372b7aed243fb31": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d4bd5559d4134d64a943d57972c6ef39": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"d7375f0f048841b29a20601c122666e8": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_331f516c7a76456d801bc2a2feb228aa",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_9be9074028da42d39d044a78393a861f",
|
||
"value": "special_tokens_map.json: 100%"
|
||
}
|
||
},
|
||
"d7f92e8332374313bee87ccd427446a4": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"da8ffc70820a48f5a12c6d4b5967015b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_8ea52b105a7e44978caca33c0e7e815b",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_3662f1445ef34a50b462e601ed31bb69",
|
||
"value": " 345/345 [00:00<00:00, 23.9kB/s]"
|
||
}
|
||
},
|
||
"e3c3bd9c4c124b0a8c88c83c1fc747d3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"e6533d3c91fd4359bc84ffd8e59af5a3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_88fcd51819b5483c9ab22df7ef89ab64",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_e6ffac074f1b476ba2ade11b37732af3",
|
||
"value": " 11.6k/11.6k [00:00<00:00, 81.5kB/s]"
|
||
}
|
||
},
|
||
"e6ffac074f1b476ba2ade11b37732af3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"e887160635cb4803b9f33845df615ec6": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"e88c33f37d6849e0b1a6b41254104cb9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_89934c4f26834f15b9889ec36fee3b65",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_e887160635cb4803b9f33845df615ec6",
|
||
"value": " 230/230 [00:00<00:00, 11.6kB/s]"
|
||
}
|
||
},
|
||
"e93d063faf984cc4aa51462418d9b57e": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"e99423a1ed3f4f72886b39368468b7c1": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"e9971d220fe24552a1e9aa299765cfb9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "DescriptionStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"ea55293415ca48a4be97c2e1e4769122": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"ecdeaab4f8c94d6dade63bb06857c969": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_e93d063faf984cc4aa51462418d9b57e",
|
||
"max": 51760,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_9d45b9a5de3e4cba9ac35ad2cb187f51",
|
||
"value": 51760
|
||
}
|
||
},
|
||
"ece66fa2f128456fa2a82b8a28d1211c": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"f433ced9bfcd4a57ba691d3c1caeed08": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_51cd9026b1664819a67712996ca97bd5",
|
||
"max": 345,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_ea55293415ca48a4be97c2e1e4769122",
|
||
"value": 345
|
||
}
|
||
},
|
||
"f4519637bb43400a80ce83505101e8a5": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"f84bfc5390054ec687c157c4d68199a6": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "danger",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_2be29a4553ad4dfea8a9bc620c81a3ae",
|
||
"max": 5702746390,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_94cbb87829d1486899e2ff6325c2ecdf",
|
||
"value": 5702745847
|
||
}
|
||
},
|
||
"f84d2fe4f1c24a34948755abf1f32b7f": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_94730f13e92a4c9aac35c2cfb21fc48c",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_620c0de28ec74f71a021a2be96dccf3a",
|
||
"value": " 51760/51760 [00:01<00:00, 52026.13 examples/s]"
|
||
}
|
||
},
|
||
"f878c2e00bc240c7b0333cce950080e1": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"f899a815142542219bde22ff792fb60c": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "1.5.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_4e7cb8e988114ed4b6fe09ff9f682dff",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_a14bc1c2130842568a5fde6698731e5f",
|
||
"value": " 44.3M/44.3M [00:00<00:00, 87.2MB/s]"
|
||
}
|
||
},
|
||
"f9b01aebcbdc48a585b7942b0ee60a2d": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"fbae6e599d1644f39e5d86efa0f9f997": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "1.2.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 0
|
||
}
|