Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
Eval Results (legacy)
Instructions to use Emanuel/twitter-emotion-deberta-v3-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Emanuel/twitter-emotion-deberta-v3-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Emanuel/twitter-emotion-deberta-v3-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Emanuel/twitter-emotion-deberta-v3-base") model = AutoModelForSequenceClassification.from_pretrained("Emanuel/twitter-emotion-deberta-v3-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5298a7ad522658adf223fbc616a5a5c151b3c9c2fe09c7293b7cb724d5373048
- Size of remote file:
- 738 MB
- SHA256:
- 5af18ebb6513b6f503acddbff051b2a5d6a7a7629dc7e35242d7336effd1ac08
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