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-ctebmsp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/mdeberta-v3-base-ctebmsp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/mdeberta-v3-base-ctebmsp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/mdeberta-v3-base-ctebmsp") model = AutoModelForSequenceClassification.from_pretrained("IIC/mdeberta-v3-base-ctebmsp") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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size 1115293932
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