Instructions to use amritpuhan/fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-swag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amritpuhan/fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-swag with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("amritpuhan/fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-swag") model = AutoModelForMultipleChoice.from_pretrained("amritpuhan/fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-swag") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efb3ce792b79e626d1543d70544bacccb89333d4af17624c4abbd9f18b2de6de
- Size of remote file:
- 738 MB
- SHA256:
- 4147ed67b3158444da90cb4d3fbf436dadc40c96e50446df8216237c4bcbefc3
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