Instructions to use SetFit/deberta-v3-large__sst2__train-16-5 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-16-5 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-16-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-5") model = AutoModelForSequenceClassification.from_pretrained("SetFit/deberta-v3-large__sst2__train-16-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from SetFit/deberta-v3-large__sst2__train-16-5: direct link, hf CLI and curl.
- Browser
- Download file 156 Bytes
-
https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-5/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://SetFit/deberta-v3-large__sst2__train-16-5/special_tokens_map.json
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curl -L -o special_tokens_map.json https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-5/resolve/main/special_tokens_map.json
156 Bytes
| {"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |