Token Classification
Transformers
PyTorch
Safetensors
Spanish
deberta-v2
text-classification
biomedical
clinical
spanish
mdeberta-v3-base
Eval Results (legacy)
Instructions to use IIC/mdeberta-v3-base-nubes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/mdeberta-v3-base-nubes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/mdeberta-v3-base-nubes")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/mdeberta-v3-base-nubes") model = AutoModelForSequenceClassification.from_pretrained("IIC/mdeberta-v3-base-nubes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (a79f7d6e2634dfdb9dc1805894b934e7aee7a942) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>4e26a11
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Add README.md
49fb285 -
Upload the tokenizer
0120be4 -
Upload the model
059f9d6 -
initial commit
5ca1bce