Instructions to use zharry29/step_benchmark_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zharry29/step_benchmark_roberta with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("zharry29/step_benchmark_roberta") model = AutoModelForMultipleChoice.from_pretrained("zharry29/step_benchmark_roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d415b83c2285d8fb1c16f7864870044d21939e7e9408329c4a5ee96eb03b8f31
- Size of remote file:
- 499 MB
- SHA256:
- c37ddaf6565a40981e9b10221386a09c2eee2fe1083d5132baae5f16332deca3
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