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:
- 57b5282f1714c5d5daee276554a87edb3057765aeaa0164824fbc8b46756597c
- Size of remote file:
- 4.47 kB
- SHA256:
- 355f13985a9e31515a3e1434263bad762a4921876fe6868f610280d271fc6504
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