Token Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
biomedical
clinical
EHR
spanish
species
Eval Results (legacy)
Instructions to use BSC-NLP4BIA/bsc-bio-ehr-es-carmen-species 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-carmen-species 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-carmen-species")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BSC-NLP4BIA/bsc-bio-ehr-es-carmen-species") model = AutoModelForTokenClassification.from_pretrained("BSC-NLP4BIA/bsc-bio-ehr-es-carmen-species", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4973facc33a6508efe74adc1402a005b441e7ac1c443f029950fe5837e71602
- Size of remote file:
- 496 MB
- SHA256:
- b26b877fb228b131d1429d1814d27e1429847d50b236b2cc4fa88d3ba02af36a
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