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:
- 68e948b5a0dc755d87ba50fbe37dcd46f58d14e635809087a3a4246a211020b5
- Size of remote file:
- 499 MB
- SHA256:
- 7aca2701828c4f8713a1e7772984ccbc14234d680f05426199ae8607aab5005b
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