Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
biomedical
clinical
eHR
spanish
roberta-large-bne
Eval Results (legacy)
text-embeddings-inference
Instructions to use IIC/roberta-large-bne-cantemist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/roberta-large-bne-cantemist with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIC/roberta-large-bne-cantemist")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/roberta-large-bne-cantemist") model = AutoModelForSequenceClassification.from_pretrained("IIC/roberta-large-bne-cantemist", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4228b5acb112febaf26117f1fed4913d004441f903efcc95b696fe596e55335d
- Size of remote file:
- 1.42 GB
- SHA256:
- 5001af5275262f0e476d983c918a966fd85255073db0390fd81f36208a4f0634
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