Token Classification
Transformers
PyTorch
Safetensors
Spanish
xlm-roberta
text-classification
biomedical
clinical
spanish
XLM_R_Galen
Eval Results (legacy)
Instructions to use IIC/XLM_R_Galen-meddocan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/XLM_R_Galen-meddocan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/XLM_R_Galen-meddocan")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/XLM_R_Galen-meddocan") model = AutoModelForSequenceClassification.from_pretrained("IIC/XLM_R_Galen-meddocan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (2e9b72d9a56b32a7cdde0a37d83e024aee7bcd9c)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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