diff --git "a/demo/Janus_colab_demo.ipynb" "b/demo/Janus_colab_demo.ipynb"
deleted file mode 100644--- "a/demo/Janus_colab_demo.ipynb"
+++ /dev/null
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- "Cloning into 'Janus'...\n",
- "remote: Enumerating objects: 35, done.\u001b[K\n",
- "remote: Counting objects: 100% (35/35), done.\u001b[K\n",
- "remote: Compressing objects: 100% (31/31), done.\u001b[K\n",
- "remote: Total 35 (delta 4), reused 35 (delta 4), pack-reused 0 (from 0)\u001b[K\n",
- "Receiving objects: 100% (35/35), 955.66 KiB | 6.73 MiB/s, done.\n",
- "Resolving deltas: 100% (4/4), done.\n"
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- "!pip install -e .\n",
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- "Obtaining file:///content/Janus\n",
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- " Preparing editable metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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- "Collecting attrdict (from janus==1.0.0)\n",
- " Downloading attrdict-2.0.1-py2.py3-none-any.whl.metadata (6.7 kB)\n",
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- "Successfully built janus\n",
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- "Successfully installed attrdict-2.0.1 janus-1.0.0\n",
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- "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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- "Building wheels for collected packages: flash-attn\n",
- " Building wheel for flash-attn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- " Created wheel for flash-attn: filename=flash_attn-2.6.3-cp310-cp310-linux_x86_64.whl size=187309225 sha256=237ef9c6157db394e1ddde4ba609a21ebb98382377a27041edc09318801a6f24\n",
- " Stored in directory: /root/.cache/pip/wheels/7e/e3/c3/89c7a2f3c4adc07cd1c675f8bb7b9ad4d18f64a72bccdfe826\n",
- "Successfully built flash-attn\n",
- "Installing collected packages: flash-attn\n",
- "Successfully installed flash-attn-2.6.3\n"
- ]
- }
- ]
- },
- {
- "cell_type": "code",
- "source": [
- "\n",
- "import torch\n",
- "from transformers import AutoModelForCausalLM\n",
- "from janus.models import MultiModalityCausalLM, VLChatProcessor\n",
- "from janus.utils.io import load_pil_images\n",
- "\n",
- "# specify the path to the model\n",
- "model_path = \"deepseek-ai/Janus-1.3B\"\n",
- "vl_chat_processor: VLChatProcessor = VLChatProcessor.from_pretrained(model_path)\n",
- "tokenizer = vl_chat_processor.tokenizer\n",
- "\n",
- "vl_gpt: MultiModalityCausalLM = AutoModelForCausalLM.from_pretrained(\n",
- " model_path, trust_remote_code=True\n",
- ")\n",
- "vl_gpt = vl_gpt.to(torch.bfloat16).cuda().eval()\n",
- "\n",
- "conversation = [\n",
- " {\n",
- " \"role\": \"User\",\n",
- " \"content\": \"\\nConvert the formula into latex code.\",\n",
- " \"images\": [\"images/equation.png\"],\n",
- " },\n",
- " {\"role\": \"Assistant\", \"content\": \"\"},\n",
- "]\n",
- "\n",
- "# load images and prepare for inputs\n",
- "pil_images = load_pil_images(conversation)\n",
- "prepare_inputs = vl_chat_processor(\n",
- " conversations=conversation, images=pil_images, force_batchify=True\n",
- ").to(vl_gpt.device)\n",
- "\n",
- "# # run image encoder to get the image embeddings\n",
- "inputs_embeds = vl_gpt.prepare_inputs_embeds(**prepare_inputs)\n",
- "\n",
- "# # run the model to get the response\n",
- "outputs = vl_gpt.language_model.generate(\n",
- " inputs_embeds=inputs_embeds,\n",
- " attention_mask=prepare_inputs.attention_mask,\n",
- " pad_token_id=tokenizer.eos_token_id,\n",
- " bos_token_id=tokenizer.bos_token_id,\n",
- " eos_token_id=tokenizer.eos_token_id,\n",
- " max_new_tokens=512,\n",
- " do_sample=False,\n",
- " use_cache=True,\n",
- ")\n",
- "\n",
- "answer = tokenizer.decode(outputs[0].cpu().tolist(), skip_special_tokens=True)\n",
- "print(f\"{prepare_inputs['sft_format'][0]}\", answer)\n"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 547,
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- },
- "id": "X7B6TWTvXxRu",
- "outputId": "072387f9-6404-48f1-bcbb-f1acddf1c77f"
- },
- "execution_count": 3,
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Python version is above 3.10, patching the collections module.\n"
- ]
- },
- {
- "output_type": "stream",
- "name": "stderr",
- "text": [
- "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/image_processing_auto.py:513: FutureWarning: The image_processor_class argument is deprecated and will be removed in v4.42. Please use `slow_image_processor_class`, or `fast_image_processor_class` instead\n",
- " warnings.warn(\n"
- ]
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "preprocessor_config.json: 0%| | 0.00/347 [00:00. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565 - if you loaded a llama tokenizer from a GGUF file you can ignore this message.\n"
- ]
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "processor_config.json: 0%| | 0.00/210 [00:00 to the tokenizer\n"
- ]
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "config.json: 0%| | 0.00/1.45k [00:00\n",
- "Convert the formula into latex code.\n",
- "\n",
- "Assistant: Sure, here is the LaTeX code for the formula:\n",
- "\n",
- "\\[ A_n = a_0 \\left[ 1 + \\frac{3}{4} \\sum_{k=1}^{n} \\left( \\frac{4}{9} \\right)^k \\right] \\]\n"
- ]
- }
- ]
- }
- ]
-}
\ No newline at end of file