Instructions to use SetFit/deberta-v3-large__sst2__train-8-0 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-8-0 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-8-0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-0") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cfbcc4b65ef36e8d64e0bd30b5b1791de9f454642feaa53435127f5639ca1a7
- Size of remote file:
- 3.06 kB
- SHA256:
- 0994a8d0fe4a105d6f8f6a167b968284d1b7473d11a9ab13d4296f5bd8c6d2d9
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