40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
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import os
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定义 README.md 的内容
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readme_content = """---
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library: transformers
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pipeline_tag: text-generation
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tags:
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- hebei-tourism
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- deepseek
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- llama
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Hebei Tourism Deepseek Model
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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.
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Usage
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You can use this model with the transformers library:
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python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("jinv2/hebei-tourism-deepseek")
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tokenizer = AutoTokenizer.from_pretrained("jinv2/hebei-tourism-deepseek")
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input_text = "介绍一下河北的旅游景点"
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inputs = tokenizer(input_text, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=200)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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"""
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定义保存路径
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save_path = "/home/mmm/桌面/deepseek/hebei_model_merged/README.md"
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写入 README.md 文件
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try:
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with open(save_path, "w", encoding="utf-8") as f:
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f.write(readme_content)
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print(f"Successfully generated README.md at {save_path}")
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except Exception as e:
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print(f"Failed to generate README.md: {e}")
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验证文件内容
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if os.path.exists(save_path):
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with open(save_path, "r", encoding="utf-8") as f:
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print("\nGenerated README.md content:")
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print(f.read())
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