Instructions to use reichenbach/bert_base_swag_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reichenbach/bert_base_swag_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("reichenbach/bert_base_swag_model") model = AutoModelForMultipleChoice.from_pretrained("reichenbach/bert_base_swag_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b55556e7d8ca382c3eebde9fce791c29a18df371157ecbbed5fe5b07e4da645
- Size of remote file:
- 3.96 kB
- SHA256:
- c06e71c7fd2cddb86bbbf9ffcdb9ec570bd2befce3e16b1fb00ab7692a334e1a
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