Instructions to use Nintw923/bert-lli-gptdetetor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nintw923/bert-lli-gptdetetor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Nintw923/bert-lli-gptdetetor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Nintw923/bert-lli-gptdetetor") model = AutoModelForSequenceClassification.from_pretrained("Nintw923/bert-lli-gptdetetor") - Notebooks
- Google Colab
- Kaggle
- This is repo of the model in my paper.
- Mostly it was trained in dataset CNNArticles and ChatGPTWritedNewsArticle See here, so it may has a better behavior on classification about news articles,but now poor in science paper.GPT-3.5 and GPT4.0 are supported.
- It only takes a few data,and needs more dataset to behave better in more text fields.You can take some articles from CNN official website or other news website and generate some news article by ChatGPT to test it.
- Mostly it was trained in dataset CNNArticles and ChatGPTWritedNewsArticle See here, so it may has a better behavior on classification about news articles,but now poor in science paper.GPT-3.5 and GPT4.0 are supported.
This is repo of the model in my paper.
Mostly it was trained in dataset CNNArticles and ChatGPTWritedNewsArticle See here, so it may has a better behavior on classification about news articles,but now poor in science paper.GPT-3.5 and GPT4.0 are supported.
It only takes a few data,and needs more dataset to behave better in more text fields.You can take some articles from CNN official website or other news website and generate some news article by ChatGPT to test it.
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