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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
readme
Browse files
README.md
CHANGED
|
@@ -23,6 +23,7 @@ model-index:
|
|
| 23 |
type: text-classification
|
| 24 |
dataset:
|
| 25 |
name: meneame_controversy
|
|
|
|
| 26 |
config: es-ES
|
| 27 |
split: test
|
| 28 |
metrics:
|
|
|
|
| 23 |
type: text-classification
|
| 24 |
dataset:
|
| 25 |
name: meneame_controversy
|
| 26 |
+
type: text-classification
|
| 27 |
config: es-ES
|
| 28 |
split: test
|
| 29 |
metrics:
|