Instructions to use zharry29/step_benchmark_xlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zharry29/step_benchmark_xlnet with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("zharry29/step_benchmark_xlnet") model = AutoModelForMultipleChoice.from_pretrained("zharry29/step_benchmark_xlnet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 508640de9e6ffa50a52e0ebe5385fe5dc1c0bf1cea3b561f6f8eda185402565f
- Size of remote file:
- 1.25 kB
- SHA256:
- 6094214f624b5f203c8452028df071aa8bfc8824e90abeffaa514ff4760d5ff9
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