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:
- 6d8e958c8c68a926f315f85e96f7b50b50d02f0bef8a2a167d473baf64908c2d
- Size of remote file:
- 3.06 kB
- SHA256:
- ea8f8fdd49cbfd9ad709b65730fe54a226bfe5969ceadeea7379897e785102f6
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