Instructions to use SetFit/deberta-v3-large__sst2__train-16-9 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-16-9 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-16-9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-9") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- edac263815155af083f66ace6b9d0497afda9433aa125148f8af1dbc873d2946
- Size of remote file:
- 3.06 kB
- SHA256:
- 67572acdb6c2f713b100af5c49cc8bd18859a5a1f1858a44b66f50f63de0e28c
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