Text Classification
Transformers
English
semeval
semeval-2026
emotion
affect-prediction
temporal-nlp
roberta
Instructions to use Haxxsh/AffectDynamics-SemEval2026Task2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Haxxsh/AffectDynamics-SemEval2026Task2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Haxxsh/AffectDynamics-SemEval2026Task2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Haxxsh/AffectDynamics-SemEval2026Task2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload best model checkpoint (epoch 14, val_r_composite_avg=0.6990)
Browse files
best-epoch=14-val_r_composite_avg=0.6990.ckpt
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