Instructions to use SetFit/deberta-v3-large__sst2__train-32-0 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-32-0 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-32-0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-32-0") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-32-0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1c7421fc4768029d6a95cc6d47bade0dd188e3020e82b88f035ad49613baf57
- Size of remote file:
- 1.74 GB
- SHA256:
- 3dc7a86c0e44d818829e37e54c9b383d0c90affff9bcd3a39cc7568c380369db
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