Instructions to use SetFit/deberta-v3-large__sst2__train-16-8 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-16-8 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-16-8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-8") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4dae792db1ac4b66fa27c9af27ca9c9753f8e6736e4c7ae8f492c1a761988a63
- Size of remote file:
- 3.06 kB
- SHA256:
- a226529183fa65a237d2ad5f3392666e3bd0aa6319bc6cb08986324659251f4d
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