Instructions to use UGARIT/grc-ner-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UGARIT/grc-ner-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="UGARIT/grc-ner-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("UGARIT/grc-ner-bert") model = AutoModelForTokenClassification.from_pretrained("UGARIT/grc-ner-bert") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d82bb0c9b001659cacbeb3f29eb1448ea78644e0360537d2ae2a64e6c050d6f
- Size of remote file:
- 449 MB
- SHA256:
- 7576e106a61a6b0676d480d84d95f161f482dffd8931e8af977d859c3223f378
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