Instructions to use devloverumar/chatgpt-content-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devloverumar/chatgpt-content-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devloverumar/chatgpt-content-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devloverumar/chatgpt-content-detector") model = AutoModelForSequenceClassification.from_pretrained("devloverumar/chatgpt-content-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d8294d2d65cc1696e207bc947a79ad441bd676de28eeadf5d5b684eafe96e8f
- Size of remote file:
- 997 MB
- SHA256:
- 427aed7230382b2b5158404c995e5872980fe2130c69627ea47f53ff92e6c0cc
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