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This behaviour is the source of the following dependency conflicts.\n", "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 17.0.0 which is incompatible.\n", "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 17.0.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0m" ] } ] }, { "cell_type": "code", "source": [ "import torch\n", "from transformers import AutoTokenizer, AutoModelForCausalLM\n", "from trl import setup_chat_format\n", "\n", "DEVICE = \"cpu\"\n", "if torch.cuda.is_available():\n", " DEVICE = \"cuda\"\n", "\n", "# The huggingface model id for Mistral-NeMo-Minitron-8B instruct model\n", "checkpoint = \"rasyosef/Mistral-NeMo-Minitron-8B-Chat\"\n", "\n", "# Download and load model and tokenizer\n", "tokenizer = AutoTokenizer.from_pretrained(checkpoint)\n", "model = AutoModelForCausalLM.from_pretrained(\n", " checkpoint,\n", " torch_dtype=torch.bfloat16,\n", " device_map=\"auto\",\n", "\n", " )" ], "metadata": { "colab": { 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"4143576d-32c0-49e7-b017-3c2202aa27e2" }, "execution_count": 2, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:81: UserWarning: \n", "Access to the secret `HF_TOKEN` has not been granted on this notebook.\n", "You will not be requested again.\n", "Please restart the session if you want to be prompted again.\n", " warnings.warn(\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "tokenizer_config.json: 0%| | 0.00/178k [00:00" ], "text/html": [ "
" ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Keyboard interruption in main thread... closing server.\n", "Killing tunnel 127.0.0.1:7860 <> https://3638cee219dc5f7066.gradio.live\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [] }, "metadata": {}, "execution_count": 7 } ], "source": [ "import gradio as gr\n", "from transformers import TextIteratorStreamer, pipeline\n", "from threading import Thread\n", "\n", "# Text generation pipeline\n", "minitron = pipeline(\n", " \"text-generation\",\n", " tokenizer=tokenizer,\n", " model=model,\n", " pad_token_id=tokenizer.eos_token_id,\n", " eos_token_id=[tokenizer.eos_token_id],\n", " device_map=DEVICE\n", ")\n", "\n", "# Function that accepts a prompt and generates text using the minitron pipeline\n", "def generate(message, chat_history, max_new_tokens):\n", "\n", " history = [\n", " {\"role\": \"system\", \"content\": \"You are Minitron, a helpful AI assistant made by Nvidia and RasYosef. User will you give you a task. Your goal is to complete the task as faithfully as you can.\"}\n", " ]\n", "\n", " for sent, received in chat_history:\n", " history.append({\"role\": \"user\", \"content\": sent})\n", " history.append({\"role\": \"assistant\", \"content\": received})\n", "\n", " history.append({\"role\": \"user\", \"content\": message})\n", " #print(history)\n", "\n", " if len(tokenizer.apply_chat_template(history)) > 512:\n", " yield \"chat history is too long\"\n", " else:\n", " # Streamer\n", " streamer = TextIteratorStreamer(tokenizer=tokenizer, skip_prompt=True, skip_special_tokens=True, timeout=300.0)\n", " thread = Thread(target=minitron, kwargs={\"text_inputs\":history, \"max_new_tokens\":max_new_tokens, \"streamer\":streamer})\n", " thread.start()\n", "\n", " generated_text = \"\"\n", " for word in streamer:\n", " generated_text += word\n", " response = generated_text.strip()\n", "\n", " yield response\n", "\n", "# Chat interface with gradio\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\"\"\"\n", " # Mistral-NeMo-Minitron-8B Chatbot Demo\n", " This chatbot was created using a finetuned version of Nvidia's Mistral-NeMo-Minitron-8B transformer model.\n", " \"\"\")\n", "\n", " tokens_slider = gr.Slider(8, 256, value=64, label=\"Maximum new tokens\", info=\"A larger `max_new_tokens` parameter value gives you longer text responses but at the cost of a slower response time.\")\n", "\n", " chatbot = gr.ChatInterface(\n", " chatbot=gr.Chatbot(height=400),\n", " fn=generate,\n", " additional_inputs=[tokens_slider],\n", " stop_btn=None,\n", " examples=[\n", " [\"Hi\"], [\"hello\"],\n", " [\"Translate the word 'cat' to German.\"],\n", " [\"Recommend me three animated movies.\"],\n", " [\"Solve this quadratic equation.\\n\\nx^2 + 3x + 2 = 0\\nwhat is the value of x?\"],\n", " [\"Implement Euclid's GCD Algorithm in python\"],\n", " [\"Write a python program that computes the least common multiple (lcm) of two positive integers. Format the code in markdown.\"],\n", " [\"Molly and Abigail want to attend a beauty and modeling contest. They both want to buy new pairs of shoes and dresses. Molly buys a pair of shoes which costs $40 and a dress which costs $160. How much should Abigail budget if she wants to spend half of what Molly spent on the pair of shoes and dress?\"],\n", " ]\n", " )\n", "\n", "demo.queue().launch(debug=True)" ] }, { "cell_type": "code", "source": [], "metadata": { "id": "9OrdBqHDq8hU" }, "execution_count": 6, "outputs": [] } ] }