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-ctebmsp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/XLM_R_Galen-ctebmsp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/XLM_R_Galen-ctebmsp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/XLM_R_Galen-ctebmsp") model = AutoModelForSequenceClassification.from_pretrained("IIC/XLM_R_Galen-ctebmsp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebaef498fc114ba3ec33829736ad9a85126e7b0525d0a258b50d76c9b6ebe892
- Size of remote file:
- 1.11 GB
- SHA256:
- dbdb4ddc19784cb9ea83e8b5f3491c5f8d1babdffb9493fcff719b5c0919ecb8
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