Token Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
text-classification
biomedical
clinical
spanish
roberta-large-bne
Eval Results (legacy)
Instructions to use IIC/roberta-large-bne-ctebmsp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/roberta-large-bne-ctebmsp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/roberta-large-bne-ctebmsp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/roberta-large-bne-ctebmsp") model = AutoModelForSequenceClassification.from_pretrained("IIC/roberta-large-bne-ctebmsp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a1d8f90bc2f2d535b6521eb3b0d75251d4a830e285ac96afd8429d57c218a10
- Size of remote file:
- 1.42 GB
- SHA256:
- 179ad3c425a75b32ae20b4c14ef1e935836a98d7e8e66c555d0e87379cedf39f
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