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:
- dbaae1b963672dc70e80cc2fdd70b73cf4248c7e4ab70aec36952dc00847207c
- Size of remote file:
- 14.6 kB
- SHA256:
- 0336176438b9ce5b2697ea463ce16fac57b35a4e0c746ad3908d45720612ba1a
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