import os
定义 README.md 的内容
readme_content = """---
library: transformers
pipeline_tag: text-generation
tags:
  - hebei-tourism
  - deepseek
  - llama
Hebei Tourism Deepseek Model
This is a fine-tuned model based on deepseek-ai/deepseek-coder-1.3b-base for providing information about tourism in Hebei, China. The model is fine-tuned using the transformers library and supports text generation tasks.
Usage
You can use this model with the transformers library:
python

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("jinv2/hebei-tourism-deepseek")
tokenizer = AutoTokenizer.from_pretrained("jinv2/hebei-tourism-deepseek")

input_text = "介绍一下河北的旅游景点"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
"""
定义保存路径
save_path = "/home/mmm/桌面/deepseek/hebei_model_merged/README.md"
写入 README.md 文件
try:
    with open(save_path, "w", encoding="utf-8") as f:
        f.write(readme_content)
    print(f"Successfully generated README.md at {save_path}")
except Exception as e:
    print(f"Failed to generate README.md: {e}")
验证文件内容
if os.path.exists(save_path):
    with open(save_path, "r", encoding="utf-8") as f:
        print("\nGenerated README.md content:")
        print(f.read())