Instructions to use SetFit/deberta-v3-large__sst2__train-16-1 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-16-1 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-16-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-1") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d5f0fa325c07847812a64f7014855ad82fab962e345f834458f6c12f2f56b31
- Size of remote file:
- 1.74 GB
- SHA256:
- da3ac4b7959c42d7c00cfd970b038f3f2cab1498048cc498ebdc85ae538c6000
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