Instructions to use SetFit/deberta-v3-large__sst2__train-8-7 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-8-7 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-8-7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-7") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a29bae7899fb4ef0a8bedbec26a5ce0cd864c22d9c252014bc76575357f36f9a
- Size of remote file:
- 1.74 GB
- SHA256:
- e3e4cbea5a75b301fab43bbc43abe10b03333ed859d2f419fbd701b5dd3ba726
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