Instructions to use SetFit/deberta-v3-large__sst2__train-8-0 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-8-0 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-8-0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-0") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9b666608567edabb7435bb190c79365b456d222b42f2a72a8c7baf404676f63
- Size of remote file:
- 1.74 GB
- SHA256:
- cdd7d1495b0fde7e8a51cb41fc8fe7b9ec07187404c4da8592512d2ab0cbf10e
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