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-nubes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/roberta-large-bne-nubes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/roberta-large-bne-nubes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/roberta-large-bne-nubes") model = AutoModelForSequenceClassification.from_pretrained("IIC/roberta-large-bne-nubes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bad42a9683f1bd1fa03eb0d18b66c12d6886074e4da2324aa77a6026745dccd
- Size of remote file:
- 1.42 GB
- SHA256:
- 06c377463271cb73b0641ca786db39279784a2860c2bce406a139c70e4a8d104
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.