Text Classification
Transformers
PyTorch
Spanish
roberta
spanish
natural-language-understanding
roberta-base
Eval Results (legacy)
text-embeddings-inference
Instructions to use PlanTL-GOB-ES/Controversy-Prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PlanTL-GOB-ES/Controversy-Prediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PlanTL-GOB-ES/Controversy-Prediction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PlanTL-GOB-ES/Controversy-Prediction") model = AutoModelForSequenceClassification.from_pretrained("PlanTL-GOB-ES/Controversy-Prediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10ecc63354c3e434d6f9f4ba12c37e4b32128944645e87aa3aaf15bdcc35b080
- Size of remote file:
- 499 MB
- SHA256:
- 66f93a3ac8dd9f6aaa5b2c4a25e7197d5ed4cba961605532491ff62d811f7795
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