Instructions to use SetFit/deberta-v3-large__sst2__train-8-5 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-8-5 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-8-5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-5") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67d3dea6ce1059d371b0ca7ca2b2a33a08c6539283be1935ccea40dc9c6375ec
- Size of remote file:
- 3.06 kB
- SHA256:
- 3ccf96aa1e05cc6eb1e174573e5165e5762650d33a97f9b5ff90b96db167a73f
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