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:
- a6f81b448ff6f998d8fc236e5990a0f1088cacc91bd8316c0643f892115a3220
- Size of remote file:
- 1.25 kB
- SHA256:
- d3d4e5ee6d825c87b6a3c55c7518bf1b60bb5ecaa47f8d4120d5f14d91de73c5
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