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", device_map="auto")# 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95aee77c877c335b2c38d32c99f5f0f81143e08f19270a69c0e743be3fcddbcc
- Size of remote file:
- 499 MB
- SHA256:
- 1974959bf513599a7fbeb12690d0fd378974b15e0ee933ad639ef5b0cefd3542
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