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:
- c68fe747644442bce12eaac8af41312e26855aabe77b647471b726cc99fa329a
- Size of remote file:
- 3.12 kB
- SHA256:
- 6e707aa3e69e8a06b8005e091c04602988b0100ebea8f89554ba5744495e2ea8
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