Instructions to use SetFit/deberta-v3-large__sst2__train-16-9 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-16-9 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-16-9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-9") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d0439a757d09cc759d67ac98ce7707982449f5dfd076171f80722b37e20fef2
- Size of remote file:
- 1.74 GB
- SHA256:
- 2b43aa1fa4628150f6cb51e821a7d2db14c7e8b4c400ce3509680647050a1b08
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