Instructions to use SetFit/deberta-v3-large__sst2__train-8-2 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-8-2 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-8-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-2") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b57e3519d5a25fe97204cdb5cf9d2a1636dd22ee6d05af9ba8b07f8ab2ebfa3
- Size of remote file:
- 3.06 kB
- SHA256:
- c2edee89e51223d4320a284cbef72e437fca3d41c848028a313cd8499820f2ed
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