Instructions to use NbAiLabArchive/test_w5_long_dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5_long_dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5_long_dataset")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5_long_dataset") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5_long_dataset") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd8a5eeea2f39fae7ecc9ab43cbd80858046276b14366a8755ffbe7c3b6ab43a
- Size of remote file:
- 499 MB
- SHA256:
- 8133314c41f173ef2bcd4479603efb25f228cc0a49f56d183ac4eb121061e128
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