Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# 加载模型和分词器
+model_name = "jinaai/reader-lm-1.5b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16).to("cuda")
+
+# 定义转换函数
+def html_to_markdown(html_content):
+    messages = [{"role": "user", "content": html_content}]
+    input_text = tokenizer.apply_chat_template(messages, tokenize=False)
+    inputs = tokenizer.encode(input_text, return_tensors="pt").to("cuda")
+    outputs = model.generate(inputs, max_new_tokens=1024, temperature=0, do_sample=False, repetition_penalty=1.08)
+    markdown_content = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return markdown_content
+
+# 创建 Gradio 接口
+iface = gr.Interface(
+    fn=html_to_markdown,
+    inputs=gr.inputs.Textbox(lines=20, label="HTML 内容"),
+    outputs=gr.outputs.Textbox(label="Markdown 内容"),
+    title="HTML 转 Markdown 转换器",
+    description="输入 HTML 内容，模型将其转换为 Markdown 格式。",
+)
+
+if __name__ == "__main__":
+    iface.launch()