Instructions to use andreas122001/bloomz-560m-academic-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreas122001/bloomz-560m-academic-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="andreas122001/bloomz-560m-academic-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("andreas122001/bloomz-560m-academic-detector") model = AutoModelForSequenceClassification.from_pretrained("andreas122001/bloomz-560m-academic-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7944f66b408d0cdeaf88e54681a74c3eec0a80cb892c595b33b3cae732e8b70e
- Size of remote file:
- 4.47 GB
- SHA256:
- e61ea2e45edfeec896776af115dabcc98703ee8cc296de762c6e7c1a1defc783
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