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:
- 39ecc46e83dd4ba2a014baa0108ac84f3b676dee539debe134705219545e3a7c
- Size of remote file:
- 3.95 kB
- SHA256:
- 1519d50d64a13f05ec4aeb53b0d63c60629ba47abca7954fc5f0613012e3df36
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