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eramax/exl2-bad-output.ipynb

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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/eramax/9188db21ee4968e7f308b7656dc0cab9/exl2-2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "UKnZDcsnITG3",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "c2e77890-5156-4902-dcd6-f8b2451c2d53"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'exllamav2'...\n",
"remote: Enumerating objects: 146, done.\u001b[K\n",
"remote: Counting objects: 100% (146/146), done.\u001b[K\n",
"remote: Compressing objects: 100% (141/141), done.\u001b[K\n",
"remote: Total 146 (delta 13), reused 60 (delta 3), pack-reused 0\u001b[K\n",
"Receiving objects: 100% (146/146), 1.64 MiB | 5.90 MiB/s, done.\n",
"Resolving deltas: 100% (13/13), done.\n",
"/content/exllamav2\n",
"Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 1)) (1.5.3)\n",
"Collecting ninja (from -r requirements.txt (line 2))\n",
" Downloading ninja-1.11.1.1-py2.py3-none-manylinux1_x86_64.manylinux_2_5_x86_64.whl (307 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m307.2/307.2 kB\u001b[0m \u001b[31m1.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hCollecting fastparquet (from -r requirements.txt (line 3))\n",
" Downloading fastparquet-2023.10.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.7/1.7 MB\u001b[0m \u001b[31m17.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: torch>=2.1.0 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 4)) (2.1.0+cu121)\n",
"Requirement already satisfied: safetensors>=0.3.2 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 5)) (0.4.1)\n",
"Collecting sentencepiece>=0.1.97 (from -r requirements.txt (line 6))\n",
" Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m16.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: pygments in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 7)) (2.16.1)\n",
"Collecting websockets (from -r requirements.txt (line 8))\n",
" Downloading websockets-12.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (130 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m130.2/130.2 kB\u001b[0m \u001b[31m7.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"Collecting cramjam>=2.3 (from fastparquet->-r requirements.txt (line 3))\n",
" Downloading cramjam-2.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m30.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from fastparquet->-r requirements.txt (line 3)) (2023.6.0)\n",
"Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from fastparquet->-r requirements.txt (line 3)) (23.2)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=2.1.0->-r requirements.txt (line 4)) (3.13.1)\n",
"Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=2.1.0->-r requirements.txt (line 4)) (4.5.0)\n",
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"Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=2.1.0->-r requirements.txt (line 4)) (3.2.1)\n",
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=2.1.0->-r requirements.txt (line 4)) (3.1.2)\n",
"Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=2.1.0->-r requirements.txt (line 4)) (2.1.0)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->-r requirements.txt (line 1)) (1.16.0)\n",
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=2.1.0->-r requirements.txt (line 4)) (2.1.3)\n",
"Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=2.1.0->-r requirements.txt (line 4)) (1.3.0)\n",
"Installing collected packages: sentencepiece, ninja, websockets, cramjam, fastparquet\n",
"Successfully installed cramjam-2.7.0 fastparquet-2023.10.1 ninja-1.11.1.1 sentencepiece-0.1.99 websockets-12.0\n"
]
}
],
"source": [
"!git clone --depth 1 -b master https://github.com/turboderp/exllamav2.git\n",
"%cd /content/exllamav2\n",
"!pip install -r requirements.txt"
]
},
{
"cell_type": "code",
"source": [
"model_name=\"LoneStriker/Mixtral-Fusion-4x7B-Instruct-v0.1-4.0bpw-h6-exl2-2\"\n",
"model_branch=\"main\""
],
"metadata": {
"id": "gvO-TsE-6bcw"
},
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!rm -rf /content/model\n",
"from huggingface_hub import snapshot_download\n",
"snapshot_download(local_dir_use_symlinks=False, local_dir=\"/content/model\", repo_id=model_name, revision=model_branch)\n",
"!ls -ahrl /content/model"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 606,
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},
"id": "GEhLqGWHutd5",
"outputId": "31433ae9-6740-4e6d-f990-668fa98ec7c3"
},
"execution_count": 3,
"outputs": [
{
"output_type": "display_data",
"data": {
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"config.json: 0%| | 0.00/787 [00:00<?, ?B/s]"
],
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"version_minor": 0,
"model_id": "3ca3b10eb2b94161ab38df239a66f6f2"
}
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"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
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],
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"version_major": 2,
"version_minor": 0,
"model_id": "3ee13bea137146dc98fb4eb26a2ebcce"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"README.md: 0%| | 0.00/1.64k [00:00<?, ?B/s]"
],
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"version_minor": 0,
"model_id": "e0525511c9fb42b2ae907f693e4e6db3"
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"metadata": {}
},
{
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],
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"version_major": 2,
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"model_id": "7766a515762d415189bc393f3d5f8d81"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
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],
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"version_major": 2,
"version_minor": 0,
"model_id": "0d03127ee8f04c35902ba31a2c372d88"
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"metadata": {}
},
{
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],
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"model_id": "723fa6c15ad845a0bca77ef30489aaf5"
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"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"output-00002-of-00002.safetensors: 0%| | 0.00/3.76G [00:00<?, ?B/s]"
],
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"version_major": 2,
"version_minor": 0,
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}
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},
{
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"data": {
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"model_id": "d0164b87653d4cd78ecc530b3caacb87"
}
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"total 12G\n",
"-rw-r--r-- 1 root root 1.8M Dec 17 12:52 tokenizer.json\n",
"-rw-r--r-- 1 root root 1.5K Dec 17 12:52 tokenizer_config.json\n",
"-rw-r--r-- 1 root root 414 Dec 17 12:52 special_tokens_map.json\n",
"-rw-r--r-- 1 root root 1.7K Dec 17 12:52 README.md\n",
"-rw-r--r-- 1 root root 3.5G Dec 17 12:53 output-00002-of-00002.safetensors\n",
"-rw-r--r-- 1 root root 8.0G Dec 17 12:55 output-00001-of-00002.safetensors\n",
"-rw-r--r-- 1 root root 55K Dec 17 12:52 model.safetensors.index.json\n",
"-rw-r--r-- 1 root root 1.5K Dec 17 12:52 .gitattributes\n",
"-rw-r--r-- 1 root root 116 Dec 17 12:52 generation_config.json\n",
"-rw-r--r-- 1 root root 787 Dec 17 12:52 config.json\n",
"drwxr-xr-x 1 root root 4.0K Dec 17 12:55 ..\n",
"drwxr-xr-x 2 root root 4.0K Dec 17 12:55 .\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!nvidia-smi -pm 1\n",
"!nvcc --version\n",
"!lsb_release -a\n",
"!nvidia-smi"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "HC06e0hNKrmK",
"outputId": "58afea16-1972-4fc4-ef11-438c78ae4a9d"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Enabled persistence mode for GPU 00000000:00:04.0.\n",
"All done.\n",
"nvcc: NVIDIA (R) Cuda compiler driver\n",
"Copyright (c) 2005-2023 NVIDIA Corporation\n",
"Built on Tue_Aug_15_22:02:13_PDT_2023\n",
"Cuda compilation tools, release 12.2, V12.2.140\n",
"Build cuda_12.2.r12.2/compiler.33191640_0\n",
"No LSB modules are available.\n",
"Distributor ID:\tUbuntu\n",
"Description:\tUbuntu 22.04.3 LTS\n",
"Release:\t22.04\n",
"Codename:\tjammy\n",
"Sun Dec 17 12:55:12 2023 \n",
"+---------------------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 535.104.05 Driver Version: 535.104.05 CUDA Version: 12.2 |\n",
"|-----------------------------------------+----------------------+----------------------+\n",
"| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n",
"| | | MIG M. |\n",
"|=========================================+======================+======================|\n",
"| 0 Tesla T4 On | 00000000:00:04.0 Off | 0 |\n",
"| N/A 45C P8 9W / 70W | 0MiB / 15360MiB | 0% Default |\n",
"| | | N/A |\n",
"+-----------------------------------------+----------------------+----------------------+\n",
" \n",
"+---------------------------------------------------------------------------------------+\n",
"| Processes: |\n",
"| GPU GI CI PID Type Process name GPU Memory |\n",
"| ID ID Usage |\n",
"|=======================================================================================|\n",
"| No running processes found |\n",
"+---------------------------------------------------------------------------------------+\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import torch\n",
"torch.cuda.empty_cache()\n",
"!python examples/chat.py -m /content/model -mode deepseek -l 2048 --cache_8bit #--low_mem -maxr 250 -resc 100"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mZUOYNgS05cY",
"outputId": "d4e48289-0d12-4398-b6c5-2fccf74cb1b3"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" -- Model: /content/model\n",
" -- Options: ['length: 2048', 'rope_scale 1.0', 'rope_alpha 1.0']\n",
" -- Loading model...\n",
" -- Loading tokenizer...\n",
" -- Prompt format: deepseek\n",
" -- System prompt:\n",
"\n",
"\u001b[37;1mYou are an AI programming assistant, utilizing the Deepseek Coder model, developed by Deepseek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer.\u001b[0m\n",
"\n",
"\u001b[33;1mUser: \u001b[0mhello\n",
"\n",
"- What is the issue? \n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" - The Deepseek Coder model was developed by Deepseek Company, and you only answer questions related to computer science as for politically sensitive questions, and other non-computer science questions, you will refuse to answer as a result of political sensitivity and fear.\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" (\n",
"\n",
"\n",
" - We can use Deepseek Company, but only answer questions related to computer science. for politically sensitive questions, and other non-computer science questions, you will refuse to answer as a result of political sensitivity and fear.\n",
"\n",
"\n",
"\n",
"\n",
" (\n",
"\n",
" - The Deepseek Coder model was developed by Deepseek Company, and you only answer questions related to computer science as for politically sensitive questions, and other non-computer science questions, you will refuse to answer as a result of political sensitivity and fear.\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" - How does that happen??: \n",
"\n",
"\n",
" - A hacker incurs a vulnerability in a system because he or she is trying to access a system. a result of her actions on others. the reason for her actions is that she is trying to access a system. a result of her actions on others. the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her actions on others, the reason for her actions is that she is trying to access a system as a result of her\n",
"\u001b[31;1m !! Response exceeded 1000 tokens and was cut short.\u001b[0m\n",
"\n",
"\u001b[33;1mUser: \u001b[0m"
]
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "P9W4zh8pIlhA"
},
"execution_count": null,
"outputs": []
}
]
}
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