Instructions to use SetFit/deberta-v3-large__sst2__train-8-8 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-8-8 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-8-8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-8") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 065c7477711df463d1d2cb43a3b3e9208286a4493aa6fd05b1700b81b674356f
- Size of remote file:
- 3.06 kB
- SHA256:
- 39d294776b2c9f2c529da81d38b33c324f90f13886f47ac1ab1854968eb13802
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