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},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/lyogavin/Anima/blob/main/air_llm/tests/test_notebooks/test_compression.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"source": [
"# install airllm"
],
"metadata": {
"id": "YYpZc-_TDK1T"
}
},
{
"cell_type": "code",
"source": [
"!pip install -U airllm"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "HnTiQnlLDKkq",
"outputId": "8c902f25-4d53-4e47-fb4a-8a60cde4029f"
},
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"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting airllm\n",
" Downloading airllm-2.6-py3-none-any.whl (33 kB)\n",
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" Downloading accelerate-0.25.0-py3-none-any.whl (265 kB)\n",
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"Collecting coloredlogs (from optimum->airllm)\n",
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"\u001b[?25hCollecting datasets (from optimum->airllm)\n",
" Downloading datasets-2.15.0-py3-none-any.whl (521 kB)\n",
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"Collecting sentencepiece!=0.1.92,>=0.1.91 (from transformers->airllm)\n",
" Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
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" Downloading pyarrow_hotfix-0.6-py3-none-any.whl (7.9 kB)\n",
"Collecting dill<0.3.8,>=0.3.0 (from datasets->optimum->airllm)\n",
" Downloading dill-0.3.7-py3-none-any.whl (115 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m13.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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" Downloading multiprocess-0.70.15-py310-none-any.whl (134 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m16.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets->optimum->airllm) (2.8.2)\n",
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets->optimum->airllm) (2023.3.post1)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets->optimum->airllm) (1.16.0)\n",
"Installing collected packages: sentencepiece, pyarrow-hotfix, humanfriendly, dill, multiprocess, coloredlogs, accelerate, datasets, optimum, airllm\n",
"Successfully installed accelerate-0.25.0 airllm-2.6 coloredlogs-15.0.1 datasets-2.15.0 dill-0.3.7 humanfriendly-10.0 multiprocess-0.70.15 optimum-1.16.1 pyarrow-hotfix-0.6 sentencepiece-0.1.99\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!pip show airllm"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "8kJzg1f2EJwD",
"outputId": "19efaf07-3fa7-4151-bc76-1adf3f2ffb70"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Name: airllm\n",
"Version: 2.6\n",
"Summary: AirLLM allows single 4GB GPU card to run 70B large language models without quantization, distillation or pruning.\n",
"Home-page: https://github.com/lyogavin/Anima/tree/main/air_llm\n",
"Author: Gavin Li\n",
"Author-email: gavinli@animaai.cloud\n",
"License: \n",
"Location: /usr/local/lib/python3.10/dist-packages\n",
"Requires: accelerate, huggingface-hub, optimum, safetensors, scipy, torch, tqdm, transformers\n",
"Required-by: \n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!cp ./*.py /usr/local/lib/python3.10/dist-packages/airllm/"
],
"metadata": {
"id": "5ILXGzUNEMOk"
},
"execution_count": 3,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!pip install bitsandbytes"
],
"metadata": {
"id": "4hswl_tqEwNI",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "29a6610b-4df3-44f6-eef6-88f863539476"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting bitsandbytes\n",
" Downloading bitsandbytes-0.41.3.post2-py3-none-any.whl (92.6 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.6/92.6 MB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hInstalling collected packages: bitsandbytes\n",
"Successfully installed bitsandbytes-0.41.3.post2\n"
]
}
]
},
{
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"outputs": [
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"name": "stdout",
"text": [
">>>> bitsandbytes installed\n"
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"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.23.safetensors\n"
]
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"\r 71%|███████▏ | 25/35 [01:14<00:15, 1.59s/it]"
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"output_type": "stream",
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"text": [
"Loading shard 2/2\n",
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.24.safetensors\n"
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"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.25.safetensors\n"
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"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.26.safetensors\n"
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"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.27.safetensors\n"
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"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.28.safetensors\n"
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"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.29.safetensors\n"
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"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.30.safetensors\n"
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"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.layers.31.safetensors\n"
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" 97%|█████████▋| 34/35 [01:42<00:01, 1.47s/it]"
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"name": "stdout",
"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/model.norm.safetensors\n"
]
},
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"text": [
"100%|██████████| 35/35 [01:42<00:00, 2.94s/it]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"saved as: /root/.cache/huggingface/hub/models--garage-bAInd--Platypus2-7B/snapshots/c27aff7201e611f301c0e19f351cbe74b1a9f1f1/splitted_model.4bit/lm_head.safetensors\n",
"new version of transfomer, no need to use BetterTransformer, try setting attn impl to sdpa...\n",
"either BetterTransformer or attn_implementation='sdpa' is available, creating model directly\n",
"not support prefetching for compression for now. loading with no prepetching mode.\n",
"new version of transfomer, no need to use BetterTransformer, try setting attn impl to sdpa...\n",
"either BetterTransformer or attn_implementation='sdpa' is available, creating model directly\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"cuda:0: 100%|██████████| 35/35 [00:23<00:00, 1.48it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"new version of transfomer, no need to use BetterTransformer, try setting attn impl to sdpa...\n",
"either BetterTransformer or attn_implementation='sdpa' is available, creating model directly\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"cuda:0: 100%|██████████| 35/35 [00:11<00:00, 3.13it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"new version of transfomer, no need to use BetterTransformer, try setting attn impl to sdpa...\n",
"either BetterTransformer or attn_implementation='sdpa' is available, creating model directly\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"cuda:0: 100%|██████████| 35/35 [00:10<00:00, 3.26it/s]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"'<s> I like to think of'"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "string"
}
},
"metadata": {},
"execution_count": 5
}
],
"source": [
"from airllm import AutoModel\n",
"\n",
"MAX_LENGTH = 128\n",
"# could use hugging face model repo id:\n",
"model = AutoModel.from_pretrained(\"garage-bAInd/Platypus2-7B\", compression='4bit' )\n",
"\n",
"input_text = [\n",
" #'What is the capital of China?',\n",
" 'I like',\n",
" ]\n",
"\n",
"input_tokens = model.tokenizer(input_text,\n",
" return_tensors=\"pt\",\n",
" return_attention_mask=False,\n",
" truncation=True,\n",
" max_length=MAX_LENGTH,\n",
" #padding=True\n",
" )\n",
"\n",
"generation_output = model.generate(\n",
" input_tokens['input_ids'].cuda(),\n",
" max_new_tokens=3,\n",
" use_cache=True,\n",
" return_dict_in_generate=True)\n",
"\n",
"model.tokenizer.decode(generation_output.sequences[0])"
]
}
]
}
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