Instructions to use SetFit/deberta-v3-large__sst2__train-32-1 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-32-1 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-32-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-32-1") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-32-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaf1fa1821cdc7c86ea43ac2dfc737ebeecc72038229d35b08c8d562a9308107
- Size of remote file:
- 1.74 GB
- SHA256:
- a88901b246c2fbf8693f0f22cdadf4b33f65f3da19ded0f60cedbde6f0ef54f2
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