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:
- 9e649e8304c2824fd09e7e8a95d6a357f6cf769b86f576454c0f4c130145ef8a
- Size of remote file:
- 2.24 GB
- SHA256:
- 2a14d36d54c719d270aa81ebfee4a5639b67b9d1e6c3c20f8da870ef41bf510d
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