Instructions to use zharry29/step_benchmark_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zharry29/step_benchmark_bert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("zharry29/step_benchmark_bert") model = AutoModelForMultipleChoice.from_pretrained("zharry29/step_benchmark_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cabedffc9941cbd05bfce19834e4a2e03e966db980d89cd03f832f770f895513
- Size of remote file:
- 438 MB
- SHA256:
- 042b80e8fecd8cf84ac3bf471ddd92b3aab9dbd34546a628ce52745a05ccc72e
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