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:
- abfcc16a4c62a9bc0319e38e71eed9d4fe391175baa529743ba2bd77a6849f03
- Size of remote file:
- 14.6 kB
- SHA256:
- 0d944d6907131fce4941c1b98753b6c6304e9268438faa750202a7ed282544a4
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