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:
- 8c4c57708d04f2550354edfdc5dd8f1ec00fa8919f0f8b1fea99393ed978365a
- Size of remote file:
- 499 MB
- SHA256:
- d84d834c3d1d18d85e72dfcc479edb09e07e76b17c38d3853a5fa965a4634781
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