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print("START: BEFORE IMPORTS") |
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import os |
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import time |
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import gradio as gr |
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import copy |
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from llama_cpp import Llama |
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from huggingface_hub import hf_hub_download |
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print("START: AFTER IMPORTS") |
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try: |
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print("START: BEFORE MODEL DOWNLOAD") |
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start_load_time = time.time() |
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model_path = hf_hub_download( |
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repo_id="NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF", |
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filename="Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf", |
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) |
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print(f"START: AFTER MODEL DOWNLOAD -- {time.time() - start_load_time}s") |
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llm = Llama( |
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model_path=model_path, |
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n_ctx=2048, |
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n_gpu_layers=-1, |
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verbose=True |
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) |
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print(f"START: AFTER LLAMA-CPP SETUP -- {time.time() - start_load_time}s") |
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except Exception as e: |
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print(e) |
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def generate_text( |
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message, |
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history: list[tuple[str, str]], |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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messages = [{"role": "system", "content": system_message}] |
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for val in history: |
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if val[0]: |
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messages.append({"role": "user", "content": val[0]}) |
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if val[1]: |
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messages.append({"role": "assistant", "content": val[1]}) |
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messages.append({"role": "user", "content": message}) |
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response = "" |
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for chunk in llm.create_chat_completion( |
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stream=True, |
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max_tokens=max_tokens, |
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temperature=temperature, |
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top_p=top_p, |
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messages=messages, |
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): |
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part = chunk["choices"][0]["delta"].get("content", None) |
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if part: |
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response += part |
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yield response |
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demo = gr.ChatInterface( |
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generate_text, |
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title="llama-cpp-python on GPU", |
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description="Running LLM with https://github.com/abetlen/llama-cpp-python", |
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examples=[ |
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["How to setup a human base on Mars? Give short answer."], |
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["Explain theory of relativity to me like I’m 8 years old."], |
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["What is 9,000 * 9,000?"], |
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["Write a pun-filled happy birthday message to my friend Alex."], |
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["Justify why a penguin might make a good king of the jungle."], |
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], |
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cache_examples=False, |
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retry_btn=None, |
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undo_btn="Delete Previous", |
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clear_btn="Clear", |
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additional_inputs=[ |
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gr.Textbox(value="You are a friendly Chatbot.", label="System message"), |
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), |
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), |
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gr.Slider( |
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minimum=0.1, |
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maximum=1.0, |
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value=0.95, |
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step=0.05, |
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label="Top-p (nucleus sampling)", |
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), |
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], |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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