Text Classification
Transformers
PyTorch
Safetensors
Spanish
xlm-roberta
biomedical
clinical
spanish
xlm-roberta-large
Eval Results (legacy)
text-embeddings-inference
Instructions to use IIC/xlm-roberta-large-caresC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/xlm-roberta-large-caresC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIC/xlm-roberta-large-caresC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/xlm-roberta-large-caresC") model = AutoModelForSequenceClassification.from_pretrained("IIC/xlm-roberta-large-caresC") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (684c62d07ac238542af6301b8d3a1690441cb8f9)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
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