Instructions to use cestwc/roberta-base-bigram-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cestwc/roberta-base-bigram-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cestwc/roberta-base-bigram-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cestwc/roberta-base-bigram-binary") model = AutoModelForTokenClassification.from_pretrained("cestwc/roberta-base-bigram-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca63cacd82528dde5fdcc794b728aeec160d17ee6859b5745f87ac36c404caa3
- Size of remote file:
- 496 MB
- SHA256:
- 17ee7a55523c57ed8f9c50c3d4d9c2bb4a00f7da92c324289874e9c872bbd3ff
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