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"\n", + "def set_css():\n", + " display(HTML('''\n", + " \n", + " '''))\n", + " display(Javascript('''\n", + " for (rule of document.styleSheets[0].cssRules){\n", + " if (rule.selectorText=='body') {\n", + " rule.style.fontSize = '22px'\n", + " break\n", + " }\n", + " }\n", + " '''))\n", + "get_ipython().events.register('pre_run_cell', set_css)" + ], + "metadata": { + "id": "45UaF7jWJ2Zk" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "## Install dependencies" + ], + "metadata": { + "id": "gRb_DgTEDOnU" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "arL34ibCDLdp", + "outputId": "d9fe4079-3932-48f5-a562-ddb125ab9736" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " Installing build dependencies ... \u001b[?25l\u001b[?25hcanceled\n", + "\u001b[31mERROR: Operation cancelled by user\u001b[0m\u001b[31m\n", + "\u001b[0m" + ] + } + ], + "source": [ + "!pip install -q sentencepiece accelerate\n", + "!pip uninstall -y transformers\n", + "!pip install -q git+https://github.com/huggingface/transformers\n", + "!pip install -q git+https://github.com/huggingface/peft\n", + "!pip install bitsandbytes" + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Download and load models" + ], + "metadata": { + "id": "iidzSXapDUvm" + } + }, + { + "cell_type": "markdown", + "source": [ + "This model is trained with guanaco dataset
\n", + "Please check https://guanaco-model.github.io/
\n", + "or https://huggingface.co/datasets/JosephusCheung/GuanacoDataset
\n", + "For more informations" + ], + "metadata": { + "id": "fyxuEaY-x8gW" + } + }, + { + "cell_type": "code", + "source": [ + "import torch\n", + "import peft\n", + "from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig\n", + "\n", + "tokenizer = LlamaTokenizer.from_pretrained(\"decapoda-research/llama-7b-hf\")\n", + "\n", + "model = LlamaForCausalLM.from_pretrained(\n", + " \"KBlueLeaf/guanaco-7b-leh-v2\",\n", + " load_in_8bit=True,\n", + " device_map=\"auto\",\n", + " torch_dtype=torch.float16\n", + ")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "referenced_widgets": [ + "c0c8654211c64af0abdb465bb0fce522", + "ddc3e87c1d704b2994a45d2fc47071e0", + "f14183b68f2943938108d444d38f5aa2", + "933cb1e5679d4db1b005bd6cd8016209", + "98c112c6490047f1996a5aa11f141778", + "e52e7a67d8a54abebeb4f6523d63d25a", + "e7a18c4b3abc4f5598dbae12272e9fa7", + "9a7d5c3690a3439b8de0535aae1e2586", + "e4afb003db074c738af3e0a2371eff13", + 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For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues\n", + "================================================================================\n", + "CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...\n", + "CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so\n", + "CUDA SETUP: Highest compute capability among GPUs detected: 7.5\n", + "CUDA SETUP: Detected CUDA version 118\n", + "CUDA SETUP: Loading binary /usr/local/lib/python3.9/dist-packages/bitsandbytes/libbitsandbytes_cuda118.so...\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /usr/lib64-nvidia did not contain libcudart.so as expected! Searching further paths...\n", + " warn(msg)\n", + "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events')}\n", + " warn(msg)\n", + "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/gpu-t4-s-2ht9r2wcptc4i --tunnel_background_save_delay=10s --tunnel_periodic_background_save_frequency=30m0s --enable_output_coalescing=true --output_coalescing_required=true'), PosixPath('--listen_host=172.28.0.12 --target_host=172.28.0.12 --tunnel_background_save_url=https')}\n", + " warn(msg)\n", + "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}\n", + " warn(msg)\n", + "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('module'), PosixPath('//ipykernel.pylab.backend_inline')}\n", + " warn(msg)\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Downloading tokenizer.model: 0%| | 0.00/500k [00:00" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "application/javascript": [ + "\n", + " for (rule of document.styleSheets[0].cssRules){\n", + " if (rule.selectorText=='body') {\n", + " rule.style.fontSize = '22px'\n", + " break\n", + " }\n", + " }\n", + " " + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "Chat like instruction" + ], + "metadata": { + "id": "7SWrtPy9Mfnn" + } + }, + { + "cell_type": "code", + "source": [ + "import os\n", + "from torch import manual_seed\n", + "\n", + "\n", + "prompt = \"\"\"### Instruction:\n", + "{}\n", + "\n", + "### Response:\"\"\"\n", + "\n", + "# instruction = \"Write a diary.\" #@param {type:\"string\"}\n", + "message = \"\\u4F60\\u525B\\u525B\\u5BEB\\u4E86\\u4EC0\\u9EBC\\uFF1F\" #@param {type:\"string\"}\n", + "system = \"\" #@param {type:\"string\"}\n", + "history_len = 5 #@param {type:\"integer\"}\n", + "ignore_last = True #@param {type:\"boolean\"}\n", + "\n", + "if ignore_last:\n", + " history = history[:-2]\n", + "\n", + "instruction = '\\n'.join(fixed_prompt+history[-(history_len*2):])\n", + "input = f'User: {message}'\n", + "if system:\n", + " input = f'{input}\\nSystem: {system}'\n", + "\n", + "if input=='':\n", + " prompt = prompt.format(instruction)\n", + "else:\n", + " prompt = prompt.format(\"{}\\n\\n### input:\\n{}\"\"\").format(instruction, input)\n", + "\n", + "inputs = tokenizer(\n", + " prompt,\n", + " return_tensors=\"pt\",\n", + ")\n", + "input_ids = inputs[\"input_ids\"].cuda()\n", + "\n", + "generation_config = GenerationConfig(\n", + " do_sample=True #@param {type:\"boolean\"}\n", + " ,temperature=0.7 #@param {type:\"number\"}\n", + " ,top_p=0.95 #@param {type:\"number\"}\n", + " ,top_k=40 #@param {type:\"number\"}\n", + " # ,num_beams=1 #@param {type:\"number\"}\n", + " ,repetition_penalty=1.13 #@param {type:\"number\"}\n", + " # ,length_penalty=-0.25 #@param {type:\"number\"}\n", + ")\n", + "\n", + "seed = 0 #@param {type:\"integer\"}\n", + "if seed == -1:\n", + " seed = int.from_bytes(os.urandom(4), 'big')\n", + "manual_seed(seed)\n", + "print(f\"Generating... Seed: {seed}\")\n", + "\n", + "print('='*40)\n", + "print('History: \\n')\n", + "print('\\n\\n'.join(fixed_prompt+history[-(history_len*2):]))\n", + "print('='*40)\n", + "if input:\n", + " print('Message:\\n')\n", + " print(input)\n", + " print('='*40)\n", + "\n", + "generation_output = model.generate(\n", + " input_ids=input_ids,\n", + " generation_config=generation_config,\n", + " return_dict_in_generate=True,\n", + " output_scores=True\n", + " ,max_new_tokens=512 #@param {type:\"integer\"}\n", + ")\n", + "\n", + "for s in generation_output.sequences:\n", + " result = tokenizer.decode(s).strip()\n", + " result = result.replace(prompt, '')\n", + " if result=='':\n", + " print('No output')\n", + " print(prompt)\n", + " print(result)\n", + " continue\n", + " print('\\nResponse: ', end='')\n", + " print(result)\n", + "\n", + " history += [f'User: {message}', f'Assistant: {result.strip()}']\n" + ], + "metadata": { + "cellView": "form", + "id": "fG3P-dnyDj_4", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 489 + }, + "outputId": "f135a1a6-0dd6-455f-8d46-5ac3b367ef7f" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "application/javascript": [ + "\n", + " for (rule of document.styleSheets[0].cssRules){\n", + " if (rule.selectorText=='body') {\n", + " rule.style.fontSize = '22px'\n", + " break\n", + " }\n", + " }\n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Generating... Seed: 0\n", + "========================================\n", + "History: \n", + "\n", + "User: 寫一篇日記。\n", + "\n", + "Assistant: 今天是一個美好的日子，陽光照耀了大地，空氣清新。我從家上出去散步，看到遊客在河岸走進水面，它讓我想起了一個很久以前的時候，我和我的朋友一起去海邊漫步，那是一件特別的回憶。我從那個時候開始學習了如何感受自然，從那個時候開始了我的愛之旅。\n", + "========================================\n", + "Message:\n", + "\n", + "User: 你剛剛寫了什麼？\n", + "========================================\n", + "\n", + "Response: \n", + "我剛剛寫了一篇日記，講述了我從家出去散步的經歷，看到遊客在河岸走進水面，它讓我想起了一個很久以前的時候，我和我的朋友一起去海邊漫步，那是一件特別的回憶。我從那個時候開始學習了如何感受自然，從那個時候開始了我的愛之旅。\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "---\n", + "Normal instruction" + ], + "metadata": { + "id": "1jVGZaPuMkvs" + } + }, + { + "cell_type": "code", + "source": [ + "import os\n", + "from torch import manual_seed\n", + "\n", + "\n", + "prompt = \"\"\"### Instruction:\n", + "{}\n", + "\n", + "### Response:\"\"\"\n", + "\n", + "instruction = \"\\u5BEB\\u4E00\\u7BC7\\u65E5\\u8A18\" #@param {type:\"string\"}\n", + "input = \"\" #@param {type:\"string\"}\n", + "\n", + "if input=='':\n", + " prompt = prompt.format(instruction)\n", + "else:\n", + " prompt = prompt.format(\"{}\\n\\n### input:\\n{}\"\"\").format(instruction, input)\n", + "\n", + "inputs = tokenizer(\n", + " prompt,\n", + " return_tensors=\"pt\",\n", + ")\n", + "input_ids = inputs[\"input_ids\"].cuda()\n", + "\n", + "generation_config = GenerationConfig(\n", + " do_sample=True #@param {type:\"boolean\"}\n", + " ,temperature=0.5 #@param {type:\"number\"}\n", + " ,top_p=0.75 #@param {type:\"number\"}\n", + " ,top_k=35 #@param {type:\"number\"}\n", + " # ,num_beams=1 #@param {type:\"number\"}\n", + " ,repetition_penalty=1.05 #@param {type:\"number\"}\n", + " # ,length_penalty=-0.25 #@param {type:\"number\"}\n", + ")\n", + "\n", + "seed = -1 #@param {type:\"integer\"}\n", + "if seed == -1:\n", + " seed = int.from_bytes(os.urandom(4), 'big')\n", + "manual_seed(seed)\n", + "print(f\"Generating... Seed: {seed}\")\n", + "print('='*40)\n", + "print('Instruction:')\n", + "print(instruction)\n", + "\n", + "if input:\n", + " print('\\nInput:')\n", + " print(input)\n", + "\n", + "generation_output = model.generate(\n", + " input_ids=input_ids,\n", + " generation_config=generation_config,\n", + " return_dict_in_generate=True,\n", + " output_scores=True\n", + " ,max_new_tokens=512 #@param {type:\"integer\"}\n", + ")\n", + "\n", + "for s in generation_output.sequences:\n", + " result = tokenizer.decode(s).strip()\n", + " result = result.replace(prompt, '')\n", + " if result=='':\n", + " print('No output')\n", + " print(prompt)\n", + " print(result)\n", + " continue\n", + " print('\\nResponse: ', end='')\n", + " print(result)\n", + "\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 239 + }, + "id": "pkZU--qvLsxB", + "outputId": "71eab04a-3429-4a2e-80db-1f2128da9296", + "cellView": "form" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "application/javascript": [ + "\n", + " for (rule of document.styleSheets[0].cssRules){\n", + " if (rule.selectorText=='body') {\n", + " rule.style.fontSize = '22px'\n", + " break\n", + " }\n", + " }\n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Generating... Seed: 4187272078\n", + "========================================\n", + "Instruction:\n", + "寫一篇日記\n", + "\n", + "Response: \n", + "今天是一個美好的日子，陽光照耀了大地，空氣清新。我從家上出去散步，看到遊客在河岸走進水面，它讓我想起了一個很久以前的時候，我和我的朋友一起去海邊漫步，那是一件特別的回憶。我從那個時候開始學習了如何感受自然，從那個時候開始了我的愛之旅。\n" + ] + } + ] + } + ] +} \ No newline at end of file