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import gradio as gr, os
from transformers import BartForConditionalGeneration
# 加载 BART 模型
model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
def generate_summary(file):
# 重置文件指针位置
file.seek(0)
# 读取上传的文本文件内容
text_content = file.read()
# 使用模型进行处理（摘要生成）
summary_ids = model.generate(text_content, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
summary = model.decode(summary_ids[0], skip_special_tokens=True)
return summary
demo = gr.Interface(
fn=generate_summary,
inputs=gr.File(),
outputs="text",
live=False
)
# 启动应用
demo.launch(share=True)
# 加载 BART 模型
model = BartForConditionalGeneration.from_pretrained("models/fnlp/bart-base-chinese")
def generate_summary(file):
# 重置文件指针位置
file.seek(0)
# 读取上传的文本文件内容
text_content = file.read()
# 使用模型进行处理（摘要生成）
summary_ids = model.generate(text_content, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
summary = model.decode(summary_ids[0], skip_special_tokens=True)
return summary
demo = gr.Interface(
fn=generate_summary,
inputs=gr.File(),
outputs="text",
live=False
)
# 启动应用
demo.launch(share=True)
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