{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "953dfc98",
   "metadata": {},
   "outputs": [],
   "source": [
    "from awq import AutoAWQForCausalLM\n",
    "from transformers import AutoTokenizer, AutoProcessor, TextStreamer\n",
    "from PIL import Image\n",
    "import requests\n",
    "import torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c667ce7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "quant_path = './llava-v1.6-34b-awq'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6adbf36e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Replacing layers...: 100%|██████████| 60/60 [00:06<00:00,  9.86it/s]\n",
      "Fusing layers...: 100%|██████████| 60/60 [00:00<00:00, 166.86it/s]\n"
     ]
    }
   ],
   "source": [
    "model = AutoAWQForCausalLM.from_quantized(quant_path, safetensors=True, device_map=\"auto\")\n",
    "processor = AutoProcessor.from_pretrained(quant_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d8ab8031",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://github.com/haotian-liu/LLaVA/blob/1a91fc274d7c35a9b50b3cb29c4247ae5837ce39/images/llava_v1_5_radar.jpg?raw=true\"\n",
    "image = Image.open(requests.get(url, stream=True).raw)\n",
    "prompt = \"<|im_start|>system\\nAnswer the questions.<|im_end|><|im_start|>user\\n<image>\\nWhat is shown in this image?<|im_end|><|im_start|>assistant\\n\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "350d6426",
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs = processor(prompt, image, return_tensors='pt').to(0, torch.float16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "24c9ac90",
   "metadata": {},
   "outputs": [],
   "source": [
    "streamer = TextStreamer(processor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "74e964aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<|im_start|> system\n",
      "Answer the questions.<|im_end|><|im_start|> user\n",
      "<image> \n",
      "What is shown in this image?<|im_end|><|im_start|> assistant\n",
      "The image shows a radar chart with various data points. The chart is a polar plot with concentric "
     ]
    }
   ],
   "source": [
    "generation_output = model.generate(**inputs,max_new_tokens=1024, streamer = streamer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ae4ca43",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
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 },
 "nbformat": 4,
 "nbformat_minor": 5
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