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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1144113931a4563add38c0221b12c87a670f4f8ec48bd0692322bf63fd6b673a
- Size of remote file:
- 627 Bytes
- SHA256:
- 41ae6308e9257a0ce7d835dbcab2c13e89f7b8a4de85435654c19865584fe6e8
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