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import gradio as gr | |
from openmind import AutoModelForCausalLM, AutoTokenizer | |
from transformers.generation.utils import GenerationConfig | |
import torch | |
def load_model(): | |
device = 'npu:0' | |
model_path = "Baichuan/Baichuan2_7b_chat_pt" | |
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) | |
model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloat16, trust_remote_code=True).to(device) | |
model.generation_config = GenerationConfig.from_pretrained(model_path) | |
return model, tokenizer | |
def chat(content, history): | |
messages = [] | |
messages.append({"role": "user", "content": content}) | |
response = model.chat(tokenizer, messages) | |
return response | |
if __name__ == "__main__": | |
model, tokenizer = load_model() | |
gr.ChatInterface(chat, | |
title="Baichuan2_7B 对话", | |
description="Baichuan 2 是百川智能推出的新一代开源大语言模型,采�?2.6 万亿 Tokens 的高质量语料训练,欢迎体验baichuan2_chat_7B模型�?, | |
examples=['解释一下“温故而知�?, '请制定一份杭州一日游计划'] | |
).queue().launch(debug=True) 1 | |
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