Token Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
biomedical
clinical
EHR
spanish
symptoms
Eval Results (legacy)
Instructions to use BSC-NLP4BIA/bsc-bio-ehr-es-symptemist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BSC-NLP4BIA/bsc-bio-ehr-es-symptemist with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BSC-NLP4BIA/bsc-bio-ehr-es-symptemist")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BSC-NLP4BIA/bsc-bio-ehr-es-symptemist") model = AutoModelForTokenClassification.from_pretrained("BSC-NLP4BIA/bsc-bio-ehr-es-symptemist") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80ea367b3f7aa9617b557508e337dd324c5c9e462ec36f87ff86b7475b11f46f
- Size of remote file:
- 3.89 kB
- SHA256:
- 7394ca59d757edfba390920a003140f3f3bc9e8e745909b322e0767c388ee644
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