Instructions to use SetFit/deberta-v3-large__sst2__train-16-6 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-16-6 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-16-6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-6") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58bbb2c08ceb8376fa1017bc7a36ac6715cb4c9db1a1aac260911b5544ebc950
- Size of remote file:
- 1.74 GB
- SHA256:
- d96824dd2270b1562c5129827a8213a309aa9cf6d8f3c7681c37a198a51cb42e
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