Instructions to use SetFit/deberta-v3-large__sst2__train-8-9 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-8-9 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-8-9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-9") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-8-9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c9eaa9367b3f9f9c9b38fa4d2998863f5d87fd7f6f08a1dc71c5bff46b3ddc8
- Size of remote file:
- 1.74 GB
- SHA256:
- b3231326f430396ce1d6fbca9bd3867b95266e920e9ecc76ddc5428f70a177d7
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