Instructions to use SetFit/deberta-v3-large__sst2__train-16-1 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-16-1 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-16-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-1") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SetFit/deberta-v3-large__sst2__train-16-1: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-1/resolve/main/training_args.bin
- Command line
-
hf download hf://SetFit/deberta-v3-large__sst2__train-16-1/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-1/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- e213a61c5f052f396e770514361a4d0efff30878bb48432c543c74b69279a456
- Size of remote file:
- 3.06 kB
- SHA256:
- 20c2e6c0d0459f5ecfc8eb329632fcf3d7fe1e0e9205f837260f1b5326a862ef
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