Instructions to use etagaca/verifai-detector-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use etagaca/verifai-detector-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="etagaca/verifai-detector-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("etagaca/verifai-detector-roberta") model = AutoModelForSequenceClassification.from_pretrained("etagaca/verifai-detector-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from etagaca/verifai-detector-roberta: direct link, hf CLI and curl.
- Browser
- Download file 1.33 kB
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https://huggingface.co/etagaca/verifai-detector-roberta/resolve/main/README.md
- Command line
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hf download hf://etagaca/verifai-detector-roberta/README.md
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curl -L -o README.md https://huggingface.co/etagaca/verifai-detector-roberta/resolve/main/README.md
1.33 kB
metadata
datasets:
- Hello-SimpleAI/HC3
language:
- en
pipeline_tag: text-classification
tags:
- chatgpt
Model Card for Hello-SimpleAI/chatgpt-detector-roberta
This model is trained on the mix of full-text and splitted sentences of answers from Hello-SimpleAI/HC3.
More details refer to arxiv: 2301.07597 and Gtihub project Hello-SimpleAI/chatgpt-comparison-detection.
The base checkpoint is roberta-base. We train it with all Hello-SimpleAI/HC3 data (without held-out) for 1 epoch.
(1-epoch is consistent with the experiments in our paper.)
Citation
Checkout this papaer arxiv: 2301.07597
@article{guo-etal-2023-hc3,
title = "How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection",
author = "Guo, Biyang and
Zhang, Xin and
Wang, Ziyuan and
Jiang, Minqi and
Nie, Jinran and
Ding, Yuxuan and
Yue, Jianwei and
Wu, Yupeng",
journal={arXiv preprint arxiv:2301.07597}
year = "2023",
}