Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
biomedical
clinical
spanish
roberta-large-bne
Eval Results (legacy)
text-embeddings-inference
Instructions to use IIC/roberta-large-bne-caresA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/roberta-large-bne-caresA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIC/roberta-large-bne-caresA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/roberta-large-bne-caresA") model = AutoModelForSequenceClassification.from_pretrained("IIC/roberta-large-bne-caresA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (e73c5e4feeb71ea79ec7ec6908f716971ec47ea6)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
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