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| import gradio as gr | |
| import shutil | |
| import copy | |
| import random | |
| import os | |
| import requests | |
| import time | |
| import sys | |
| from huggingface_hub.file_download import http_get | |
| from llama_cpp import Llama | |
| SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им." | |
| def get_message_tokens(model, role, content): | |
| content = f"{role}\n{content}\n</s>" | |
| content = content.encode("utf-8") | |
| return model.tokenize(content, special=True) | |
| def get_system_tokens(model): | |
| system_message = {"role": "system", "content": SYSTEM_PROMPT} | |
| return get_message_tokens(model, **system_message) | |
| directory = "." | |
| model_url = "https://huggingface.co/IlyaGusev/saiga_mistral_7b_gguf/resolve/main/model-q4_K.gguf" | |
| model_name = "model-q4_K.gguf" | |
| final_model_path = os.path.join(directory, model_name) | |
| print("Downloading all files...") | |
| rm_files = [os.path.join(directory, f) for f in os.listdir(directory)] | |
| for f in rm_files: | |
| if os.path.isfile(f): | |
| os.remove(f) | |
| else: | |
| shutil.rmtree(f) | |
| if not os.path.exists(final_model_path): | |
| with open(final_model_path, "wb") as f: | |
| http_get(model_url, f) | |
| os.chmod(final_model_path, 0o777) | |
| print("Files downloaded!") | |
| model = Llama( | |
| model_path=final_model_path, | |
| verbose=True, | |
| use_mmap=True, | |
| use_mlock=False, | |
| n_ctx=2000, | |
| ) | |
| print("Model loaded!") | |
| max_new_tokens = 1500 | |
| def user(message, history): | |
| new_history = history + [[message, None]] | |
| return "", new_history | |
| def bot( | |
| history, | |
| system_prompt, | |
| top_p, | |
| top_k, | |
| temp | |
| ): | |
| tokens = get_system_tokens(model)[:] | |
| for user_message, bot_message in history[:-1]: | |
| message_tokens = get_message_tokens(model=model, role="user", content=user_message) | |
| tokens.extend(message_tokens) | |
| if bot_message: | |
| message_tokens = get_message_tokens(model=model, role="bot", content=bot_message) | |
| tokens.extend(message_tokens) | |
| last_user_message = history[-1][0] | |
| message_tokens = get_message_tokens(model=model, role="user", content=last_user_message) | |
| tokens.extend(message_tokens) | |
| role_tokens = model.tokenize("bot\n".encode("utf-8"), special=True) | |
| tokens.extend(role_tokens) | |
| generator = model.generate( | |
| tokens, | |
| top_k=top_k, | |
| top_p=top_p, | |
| temp=temp | |
| ) | |
| partial_text = "" | |
| for i, token in enumerate(generator): | |
| if token == model.token_eos() or (max_new_tokens is not None and i >= max_new_tokens): | |
| break | |
| partial_text += model.detokenize([token]).decode("utf-8", "ignore") | |
| history[-1][1] = partial_text | |
| yield history | |
| with gr.Blocks( | |
| theme=gr.themes.Soft() | |
| ) as demo: | |
| favicon = '<img src="https://cdn.midjourney.com/b88e5beb-6324-4820-8504-a1a37a9ba36d/0_1.png" width="48px" style="display: inline">' | |
| gr.Markdown( | |
| f"""<h1><center>{favicon}Saiga Mistral 7B GGUF Q4_K</center></h1> | |
| This is a demo of a **Russian**-speaking Mistral-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). | |
| Это демонстрационная версия [квантованной Сайги/Мистраль с 7 миллиардами параметров](https://huggingface.co/IlyaGusev/saiga_mistral_7b_gguf), работающая на CPU. | |
| Сайга — это разговорная языковая модель, дообученная 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). | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=5): | |
| system_prompt = gr.Textbox(label="Системный промпт", placeholder="", value=SYSTEM_PROMPT, interactive=False) | |
| chatbot = gr.Chatbot(label="Диалог").style(height=400) | |
| with gr.Column(min_width=80, scale=1): | |
| with gr.Tab(label="Параметры генерации"): | |
| top_p = gr.Slider( | |
| minimum=0.0, | |
| maximum=1.0, | |
| value=0.9, | |
| step=0.05, | |
| interactive=True, | |
| label="Top-p", | |
| ) | |
| top_k = gr.Slider( | |
| minimum=10, | |
| maximum=100, | |
| value=30, | |
| step=5, | |
| interactive=True, | |
| label="Top-k", | |
| ) | |
| temp = gr.Slider( | |
| minimum=0.0, | |
| maximum=2.0, | |
| value=0.01, | |
| step=0.01, | |
| interactive=True, | |
| label="Температура" | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| msg = gr.Textbox( | |
| label="Отправить сообщение", | |
| placeholder="Отправить сообщение", | |
| show_label=False, | |
| ).style(container=False) | |
| with gr.Column(): | |
| with gr.Row(): | |
| submit = gr.Button("Отправить") | |
| stop = gr.Button("Остановить") | |
| clear = gr.Button("Очистить") | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ПРЕДУПРЕЖДЕНИЕ: Модель может генерировать фактически или этически некорректные тексты. Мы не несём за это ответственность.""" | |
| ) | |
| # Pressing Enter | |
| submit_event = msg.submit( | |
| fn=user, | |
| inputs=[msg, chatbot], | |
| outputs=[msg, chatbot], | |
| queue=False, | |
| ).success( | |
| fn=bot, | |
| inputs=[ | |
| chatbot, | |
| system_prompt, | |
| top_p, | |
| top_k, | |
| temp | |
| ], | |
| outputs=chatbot, | |
| queue=True, | |
| ) | |
| # Pressing the button | |
| submit_click_event = submit.click( | |
| fn=user, | |
| inputs=[msg, chatbot], | |
| outputs=[msg, chatbot], | |
| queue=False, | |
| ).success( | |
| fn=bot, | |
| inputs=[ | |
| chatbot, | |
| system_prompt, | |
| top_p, | |
| top_k, | |
| temp | |
| ], | |
| outputs=chatbot, | |
| queue=True, | |
| ) | |
| # Stop generation | |
| stop.click( | |
| fn=None, | |
| inputs=None, | |
| outputs=None, | |
| cancels=[submit_event, submit_click_event], | |
| queue=False, | |
| ) | |
| # Clear history | |
| clear.click(lambda: None, None, chatbot, queue=False) | |
| demo.queue(max_size=128, concurrency_count=1) | |
| demo.launch() | |