Instructions to use HiTZ/BERnaT-base-NERC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/BERnaT-base-NERC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HiTZ/BERnaT-base-NERC")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HiTZ/BERnaT-base-NERC") model = AutoModelForTokenClassification.from_pretrained("HiTZ/BERnaT-base-NERC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c639efbcf2223c4af0324329b4a329a95652dc4148119c8b0b1dc7491cf0924
- Size of remote file:
- 495 MB
- SHA256:
- 6976419acf0e6a3fcdd2955006c4ece17d0c71ed823f899a22c566906a5dbb3b
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