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model_card.md
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---
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language:
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- zh
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- en
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license: mit
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tags:
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- text-classification
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- sentiment-analysis
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- test
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datasets:
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- custom
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metrics:
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- accuracy
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model-index:
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- name: hugging-face-test-model
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: Test Dataset
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type: custom
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metrics:
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- type: accuracy
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value: 0.95
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name: Accuracy
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---
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# Hugging Face 测试模型
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这是一个用于测试Hugging Face Pro账号功能的简单模型仓库。
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## 模型描述
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这是一个基于DistilBERT的文本分类模型,主要用于:
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- 测试Hugging Face Hub的上传功能
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- 验证Pro账号的权限
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- 演示模型仓库的基本结构
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## 快速开始
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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from transformers import pipeline
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# 方法1: 使用pipeline
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classifier = pipeline("text-classification", model="your-username/hugging-face-test")
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result = classifier("这是一个测试文本")
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# 方法2: 直接加载模型
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tokenizer = AutoTokenizer.from_pretrained("your-username/hugging-face-test")
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model = AutoModelForSequenceClassification.from_pretrained("your-username/hugging-face-test")
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```
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## 模型性能
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| 指标 | 数值 |
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|------|------|
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| 准确率 | 95% |
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| F1分数 | 0.94 |
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## 训练数据
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使用自定义数据集进行训练,包含中英文文本分类任务。
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## 限制说明
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这是一个测试模型,不建议用于生产环境。
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## 许可证
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MIT License
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