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:
- d5864d6e4b3df71a083c65ada8f080335c7a79e71ce516143af8c80f28be45a8
- Size of remote file:
- 469 MB
- SHA256:
- fe59bfee020f1f01137bd866d2fd2212966b7c1fabac8d963fca3376e55635ae
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