Token Classification
Transformers
Safetensors
Spanish
bert
ner
named-entity-recognition
spanish
español
biomedical
clinical
medical
oncology
prostate-cancer
cancer-de-prostata
beto
Eval Results (legacy)
Instructions to use ralzate/beto-prostata-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ralzate/beto-prostata-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ralzate/beto-prostata-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ralzate/beto-prostata-ner") model = AutoModelForTokenClassification.from_pretrained("ralzate/beto-prostata-ner") - Notebooks
- Google Colab
- Kaggle
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