Instructions to use diwank/silicone-deberta-pair with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diwank/silicone-deberta-pair with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="diwank/silicone-deberta-pair")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("diwank/silicone-deberta-pair") model = AutoModelForSequenceClassification.from_pretrained("diwank/silicone-deberta-pair", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from diwank/silicone-deberta-pair: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/diwank/silicone-deberta-pair/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://diwank/silicone-deberta-pair/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/diwank/silicone-deberta-pair/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- 4d0720c299d755699648f9fa939374e2b186d1d46f4672f0531e576bf766385c
- Size of remote file:
- 557 MB
- SHA256:
- 5db7f9ad8f01b100cf59381f38721c16eab529fe8dfc158e01b6a0abba52c970
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