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Model: jinvbar/hebei-tourism-deepseek
Source: Original Platform

generate_readme.py

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+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())