Token Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
biomedical
clinical
EHR
spanish
humans
Eval Results (legacy)
Instructions to use BSC-NLP4BIA/bsc-bio-ehr-es-carmen-humano 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-humano 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-humano")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BSC-NLP4BIA/bsc-bio-ehr-es-carmen-humano") model = AutoModelForTokenClassification.from_pretrained("BSC-NLP4BIA/bsc-bio-ehr-es-carmen-humano", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
3fb78fd
1
Parent(s): bb1a8bd
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (1f4c34c9573436cc314b1649494b71a92ccfac97)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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