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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fba494aebca5017c4f9fce06d29ceda0fa9051129783eebdf1f7d136f726525a
- Size of remote file:
- 3.06 kB
- SHA256:
- 14d943033d11a61ca040b166b2af81775506f402062e91be2db941bde1fe3076
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