Token Classification
Transformers
PyTorch
Safetensors
Spanish
xlm-roberta
text-classification
biomedical
clinical
spanish
xlm-roberta-large
Eval Results (legacy)
Instructions to use IIC/xlm-roberta-large-nubes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/xlm-roberta-large-nubes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/xlm-roberta-large-nubes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/xlm-roberta-large-nubes") model = AutoModelForSequenceClassification.from_pretrained("IIC/xlm-roberta-large-nubes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4aac5e24761fe4062505a981d873f0335e60e9575d471f54a986d69a8b6e34be
- Size of remote file:
- 2.24 GB
- SHA256:
- 5ee19b83c8d5142fc2f97a51d702e0922d66d314f3dd0ddb258c5d888b4bfddc
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