Instructions to use ProceduralTree/HW3_long_training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProceduralTree/HW3_long_training with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("ProceduralTree/HW3_long_training") model = AutoModelForMultipleChoice.from_pretrained("ProceduralTree/HW3_long_training") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41314148a92740bd8e057726b9b70e00f9328f6b9510c2e7a2be67e3c35c4b32
- Size of remote file:
- 409 MB
- SHA256:
- abfed05a4c2a2b66391e3be99882cd0f8ecef0d5631d78ccadb6261904da7346
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