Instructions to use NbAiLabArchive/test_w5_long_roberta_tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5_long_roberta_tokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5_long_roberta_tokenizer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5_long_roberta_tokenizer") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5_long_roberta_tokenizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4eb11178ddd0b7298043b5130bc6d93e8e7bac534676b855ce17aadc71073e8
- Size of remote file:
- 499 MB
- SHA256:
- 313fc5d048c0a32260622dd09f1647acf167a9816dbaa9bdb8b30fa1234e7376
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