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import gradio as gr |
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import copy |
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import random |
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import os |
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import requests |
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import time |
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import sys |
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from huggingface_hub import snapshot_download |
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from llama_cpp import Llama |
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SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им." |
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def get_message_tokens(model, role, content): |
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content = f"{role}\n{content}\n</s>" |
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content = content.encode("utf-8") |
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return model.tokenize(content, special=True) |
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def get_system_tokens(model): |
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system_message = {"role": "system", "content": SYSTEM_PROMPT} |
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return get_message_tokens(model, **system_message) |
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def load_model( |
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directory: str = ".", |
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model_name: str = "model-q4_K.gguf", |
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model_url: str = "https://huggingface.co/IlyaGusev/saiga2_13b_gguf/resolve/main/model-q4_K.gguf" |
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): |
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final_model_path = os.path.join(directory, model_name) |
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print("Downloading all files...") |
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if not os.path.exists(final_model_path): |
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with open(final_model_path, "wb") as f: |
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http_get(model_url, f) |
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os.chmod(final_model_path, 0o777) |
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print("Files downloaded!") |
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model = Llama( |
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model_path=final_model_path, |
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n_ctx=2048 |
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) |
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print("Model loaded!") |
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return model |
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MODEL = load_model() |
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def user(message, history): |
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new_history = history + [[message, None]] |
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return "", new_history |
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def bot( |
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history, |
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system_prompt, |
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top_p, |
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top_k, |
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temp |
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): |
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model = MODEL |
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tokens = get_system_tokens(model)[:] |
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tokens.append(LINEBREAK_TOKEN) |
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for user_message, bot_message in history[:-1]: |
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message_tokens = get_message_tokens(model=model, role="user", content=user_message) |
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tokens.extend(message_tokens) |
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if bot_message: |
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message_tokens = get_message_tokens(model=model, role="bot", content=bot_message) |
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tokens.extend(message_tokens) |
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last_user_message = history[-1][0] |
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message_tokens = get_message_tokens(model=model, role="user", content=last_user_message) |
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tokens.extend(message_tokens) |
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role_tokens = [model.token_bos(), BOT_TOKEN, LINEBREAK_TOKEN] |
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tokens.extend(role_tokens) |
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generator = model.generate( |
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tokens, |
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top_k=top_k, |
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top_p=top_p, |
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temp=temp |
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) |
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partial_text = "" |
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for i, token in enumerate(generator): |
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if token == model.token_eos(): |
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break |
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partial_text += model.detokenize([token]).decode("utf-8", "ignore") |
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history[-1][1] = partial_text |
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yield history |
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with gr.Blocks( |
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theme=gr.themes.Soft() |
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) as demo: |
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favicon = '<img src="https://cdn.midjourney.com/b88e5beb-6324-4820-8504-a1a37a9ba36d/0_1.png" width="48px" style="display: inline">' |
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gr.Markdown( |
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f"""<h1><center>{favicon}Saiga2 13B GGUF Q4_K</center></h1> |
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This is a demo of a **Russian**-speaking LLaMA2-based model. If you are interested in other languages, please check other models, such as [MPT-7B-Chat](https://huggingface.co/spaces/mosaicml/mpt-7b-chat). |
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Это демонстрационная версия [квантованной Сайги-2 с 13 миллиардами параметров](https://huggingface.co/IlyaGusev/saiga2_13b_ggml), работающая на CPU. |
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Сайга-2 — это разговорная языковая модель, которая основана на [LLaMA-2](https://ai.meta.com/llama/) и дообучена на корпусах, сгенерированных ChatGPT, таких как [ru_turbo_alpaca](https://huggingface.co/datasets/IlyaGusev/ru_turbo_alpaca), [ru_turbo_saiga](https://huggingface.co/datasets/IlyaGusev/ru_turbo_saiga) и [gpt_roleplay_realm](https://huggingface.co/datasets/IlyaGusev/gpt_roleplay_realm). |
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""" |
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) |
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with gr.Row(): |
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with gr.Column(scale=5): |
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system_prompt = gr.Textbox(label="Системный промпт", placeholder="", value=SYSTEM_PROMPT, interactive=False) |
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chatbot = gr.Chatbot(label="Диалог").style(height=400) |
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with gr.Column(min_width=80, scale=1): |
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with gr.Tab(label="Параметры генерации"): |
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top_p = gr.Slider( |
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minimum=0.0, |
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maximum=1.0, |
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value=0.9, |
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step=0.05, |
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interactive=True, |
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label="Top-p", |
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) |
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top_k = gr.Slider( |
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minimum=10, |
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maximum=100, |
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value=30, |
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step=5, |
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interactive=True, |
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label="Top-k", |
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) |
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temp = gr.Slider( |
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minimum=0.0, |
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maximum=2.0, |
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value=0.01, |
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step=0.01, |
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interactive=True, |
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label="Температура" |
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) |
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with gr.Row(): |
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with gr.Column(): |
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msg = gr.Textbox( |
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label="Отправить сообщение", |
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placeholder="Отправить сообщение", |
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show_label=False, |
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).style(container=False) |
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with gr.Column(): |
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with gr.Row(): |
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submit = gr.Button("Отправить") |
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stop = gr.Button("Остановить") |
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clear = gr.Button("Очистить") |
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with gr.Row(): |
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gr.Markdown( |
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"""ПРЕДУПРЕЖДЕНИЕ: Модель может генерировать фактически или этически некорректные тексты. Мы не несём за это ответственность.""" |
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) |
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submit_event = msg.submit( |
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fn=user, |
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inputs=[msg, chatbot], |
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outputs=[msg, chatbot], |
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queue=False, |
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).success( |
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fn=bot, |
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inputs=[ |
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chatbot, |
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system_prompt, |
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top_p, |
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top_k, |
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temp |
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], |
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outputs=chatbot, |
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queue=True, |
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) |
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submit_click_event = submit.click( |
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fn=user, |
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inputs=[msg, chatbot], |
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outputs=[msg, chatbot], |
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queue=False, |
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).success( |
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fn=bot, |
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inputs=[ |
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chatbot, |
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system_prompt, |
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top_p, |
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top_k, |
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temp |
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], |
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outputs=chatbot, |
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queue=True, |
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) |
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stop.click( |
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fn=None, |
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inputs=None, |
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outputs=None, |
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cancels=[submit_event, submit_click_event], |
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queue=False, |
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) |
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clear.click(lambda: None, None, chatbot, queue=False) |
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demo.queue(max_size=128, concurrency_count=1) |
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demo.launch() |
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