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-ctebmsp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/xlm-roberta-large-ctebmsp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/xlm-roberta-large-ctebmsp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/xlm-roberta-large-ctebmsp") model = AutoModelForSequenceClassification.from_pretrained("IIC/xlm-roberta-large-ctebmsp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4147f4cc5e73120e300f95a716d5346e703e5d93ba6dc9a8e301c33b7696487b
- Size of remote file:
- 2.24 GB
- SHA256:
- 461f530274ff6a319c9a31e4aa3936d010c7092968c476a16dde1c6da6b08855
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