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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 753b0b4b4165d409460bc8f94dddda46861bcfa167e7bdc95516099d3201dcc9
- Size of remote file:
- 1.74 GB
- SHA256:
- e44acf52b53908464bd7b57935fa05e87cf1898f0824ec6d7cee4a5f73589c78
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