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:
- b84cc8f66e047678623ff105754a496e042397fc0d7f6b4a2cebd4a404ed7cdd
- Size of remote file:
- 3.45 kB
- SHA256:
- cf25998c2d2a78e22dc7450ad504f2cb59548518b1a70670379b2359dcee26c1
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