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:
- 7a5a0bff5500d0c5e9f3ecfce15295ea036204b2735498a5d2c5ec0267ef403b
- Size of remote file:
- 499 MB
- SHA256:
- 020880601f0315d7f25118bb4e03687096b7925f819cc66ae96fe4e5886b99c3
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