Instructions to use SetFit/deberta-v3-large__sst2__train-16-2 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-16-2 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-16-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-2") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d4475854ed2e10a1007546de515287de03ae1fb1326da624a3edbf462db095b
- Size of remote file:
- 3.06 kB
- SHA256:
- 317b5f70ac739c58a8cfbeb2c8d7a81f3122f239bd3d80286618ab0b419aa461
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