Instructions to use NbAiLabArchive/test_w5_long with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5_long with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5_long")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5_long") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5_long") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1612134d4960a60c31e66fb39e60107a4c933dbbf4d88f847740c7866ab058f6
- Size of remote file:
- 499 MB
- SHA256:
- be40fbd89d801303cc4d630bc2f0e2771d3b16847fb12c736bbe30a997a563b6
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