Instructions to use kwang2049/SBERT-base-nli-stsb-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kwang2049/SBERT-base-nli-stsb-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kwang2049/SBERT-base-nli-stsb-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kwang2049/SBERT-base-nli-stsb-v2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/kwang2049/SBERT-base-nli-stsb-v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kwang2049/SBERT-base-nli-stsb-v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kwang2049/SBERT-base-nli-stsb-v2/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- eef63bebaf805e475f2d2ff85eb62a917fd0a529ca42992436ae39517714bd14
- Size of remote file:
- 438 MB
- SHA256:
- 8a40ae39559975dc44aa3f23acc419ca7cc24ac0135adf3879ba480a1a4439dd
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