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:
- 7025d6321855c6df0d1c9865c9b85bac0fbc5aea7b2a0950d28ad15f78cd5548
- Size of remote file:
- 4.47 GB
- SHA256:
- 5e6bf3bde909bd33d0b254dc94556f1eff9f965c1d44cbf806d02a903084b53c
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