Instructions to use XiweiZ/sts-ft-biased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use XiweiZ/sts-ft-biased with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("XiweiZ/sts-ft-biased") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - setfit
How to use XiweiZ/sts-ft-biased with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("XiweiZ/sts-ft-biased") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from XiweiZ/sts-ft-biased: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/XiweiZ/sts-ft-biased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://XiweiZ/sts-ft-biased/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/XiweiZ/sts-ft-biased/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- e5b35318b9216a0beffa5f1302e7af182afd3b1311c9036d3517d25361ebdb07
- Size of remote file:
- 438 MB
- SHA256:
- 85ff07df7f0f0a6ccc00ae349aa718ace7f9ca24d719afbd81ed2dd6ba2ef795
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