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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f91ede1d67bc8d8e67b43937bd99d3d7f1457eb658cd7be5424bc722a5444f1
- Size of remote file:
- 14.5 MB
- SHA256:
- fa18280d17cb2240255ae226f2e8ce87bc72ae3fb9f7044d0238395b4d8b7a33
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