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-ehealth_kd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/mdeberta-v3-base-ehealth_kd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/mdeberta-v3-base-ehealth_kd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/mdeberta-v3-base-ehealth_kd") model = AutoModelForSequenceClassification.from_pretrained("IIC/mdeberta-v3-base-ehealth_kd", 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 (4175e5eebea157b0b3d04abde359ca7f6f790947) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>2ee8cbd
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initial commit
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