Instructions to use certainstar/Trained-English-classification-case with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use certainstar/Trained-English-classification-case with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="certainstar/Trained-English-classification-case")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("certainstar/Trained-English-classification-case") model = AutoModelForSequenceClassification.from_pretrained("certainstar/Trained-English-classification-case") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: mit
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- 本模型采取 `HC3的英文数据集` 对 `bert-base-cased` 模型进行三轮训练得到结果。
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- 其作用是对文本是否为 `GPT` 生成进行分类,所得 `Label` 为0,则不为 `GPT` 生成,反之为1,则是。
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license: mit
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datasets:
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- Hello-SimpleAI/HC3
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language:
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- en
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metrics:
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- accuracy
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---
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- 本模型采取 `HC3的英文数据集` 对 `bert-base-cased` 模型进行三轮训练得到结果。
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- 其作用是对文本是否为 `GPT` 生成进行分类,所得 `Label` 为0,则不为 `GPT` 生成,反之为1,则是。
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