Instructions to use devanshrj/scideberta-cs-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devanshrj/scideberta-cs-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="devanshrj/scideberta-cs-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("devanshrj/scideberta-cs-ner") model = AutoModelForTokenClassification.from_pretrained("devanshrj/scideberta-cs-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac088f3ba5dbb2f17fc15dc2e3eb86044fccb0069450dccac54e873afdaecc80
- Size of remote file:
- 555 MB
- SHA256:
- c4cf66fd9896c1f21c54a60e9f28c05f74661d1d3a9aff248f75dca968f35a9a
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