Instructions to use SetFit/deberta-v3-large__sst2__train-16-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SetFit/deberta-v3-large__sst2__train-16-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SetFit/deberta-v3-large__sst2__train-16-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-5") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Add base_model information to model (#1)
- Librarian Bot: Add base_model information to model (e99665609ad3fb75a2af598f1a35632d6b033d4c) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>fecde5d
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update model card README.md
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Checkpoint for WandB run: deberta__train-16-5
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initial commit
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