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:
- 5fde07c9080e26246967ae629be81758b1138051d34b488661406f0c6d57ad49
- Size of remote file:
- 499 MB
- SHA256:
- 6b6c2c14c3e4a882f6733e49d27826c2a388f2425fb696e8adb66f4304d33379
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