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cf1158a 03a4ce1 3940861 cf1158a 03a4ce1 3940861 cf1158a 03a4ce1 3940861 03a4ce1 69b3e47 3940861 cf1158a 1119952 cf1158a 1119952 cf1158a 1119952 cf1158a 3940861 cf1158a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | import gradio as gr
import torch
import os
from transformers import AutoTokenizer, AutoModelForCausalLM
# 本地模型路径（绝对路径）
LOCAL_MODEL_PATH = os.path.join(os.getcwd(), "model")
print("Loading model from:", LOCAL_MODEL_PATH)
# 加载 tokenizer 和模型
tokenizer = AutoTokenizer.from_pretrained(
LOCAL_MODEL_PATH,
local_files_only=True,
trust_remote_code=False
)
model = AutoModelForCausalLM.from_pretrained(
LOCAL_MODEL_PATH,
local_files_only=True,
trust_remote_code=False,
torch_dtype=torch.float16
).to("cuda" if torch.cuda.is_available() else "cpu")
# 聊天函数
def chat(user_input):
inputs = tokenizer(user_input, return_tensors="pt").to(model.device)
outputs = model.generate(
input_ids=inputs["input_ids"],
attention_mask=inputs.get("attention_mask"),
max_new_tokens=200,
temperature=0.7,
top_p=0.9,
do_sample=True
)
return tokenizer.decode(outputs[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)
# Gradio 网页界面
interface = gr.Interface(
fn=chat,
inputs=gr.Textbox(lines=3, label="输入你的问题"),
outputs=gr.Textbox(lines=10, label="模型回答"),
title="我的AI模型",
description="在 HuggingFace Space 上运行的 LLaMA/GPT 模型网页"
)
interface.launch()
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