Instructions to use dccuchile/roberta-base-bne-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dccuchile/roberta-base-bne-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dccuchile/roberta-base-bne-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dccuchile/roberta-base-bne-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("dccuchile/roberta-base-bne-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb6cae2b8f082aa138c2eab0d886188acc7a474f7dcadf4cb5be61129939bb46
- Size of remote file:
- 2.99 kB
- SHA256:
- a7f8f9a5fef1daafc1356cf98f288ddd52b1389b48fdd675f7af45f39da88b34
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