Token Classification
Transformers
PyTorch
Safetensors
Spanish
bert
text-classification
biomedical
clinical
spanish
BETO_Galen
Eval Results (legacy)
Instructions to use IIC/BETO_Galen-meddocan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/BETO_Galen-meddocan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/BETO_Galen-meddocan")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/BETO_Galen-meddocan") model = AutoModelForSequenceClassification.from_pretrained("IIC/BETO_Galen-meddocan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33e8b9f959c350e0e350ff293cc93039d021ea20d5914a44e72342c44f956c51
- Size of remote file:
- 440 MB
- SHA256:
- 16a46d37fce2f4dab6ba81dd66fd80ff03e190c9ef20213bbb1b6b119879d122
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