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:
- b8534349fabd2f1d2226afc5056d22426eb8ae4c6e04288bcbdb7a0db53e9bbe
- Size of remote file:
- 2.93 kB
- SHA256:
- 136ac90e71a78e77c3d82ab04e27f5956ac7742f191d7fd4cc0280ff0f14814b
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