Instructions to use Supreeth/DeBERTa-Twitter-Emotion-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Supreeth/DeBERTa-Twitter-Emotion-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Supreeth/DeBERTa-Twitter-Emotion-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Supreeth/DeBERTa-Twitter-Emotion-Classification") model = AutoModelForSequenceClassification.from_pretrained("Supreeth/DeBERTa-Twitter-Emotion-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c2175ccb4b17248b72bf26a580432b77eefb25929815b37a1c014c430a6aa01
- Size of remote file:
- 557 MB
- SHA256:
- 5bc3100fb5e7ae8e5dfd57f7801465ffb49f8f960a31a2c6f86fdee07b84f920
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