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 model_head.pkl from XiweiZ/sts-ft-biased: direct link, hf CLI and curl.
- Browser
- Download file 19.4 kB
-
https://huggingface.co/XiweiZ/sts-ft-biased/resolve/main/model_head.pkl
- Command line
-
hf download hf://XiweiZ/sts-ft-biased/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/XiweiZ/sts-ft-biased/resolve/main/model_head.pkl
19.4 kB
- Xet hash:
- 3f170381213040a18916bac4fa10b675e731ba3fb0e3f48c94574e7658a7d43f
- Size of remote file:
- 19.4 kB
- SHA256:
- c434509e6adb26237ae61240b1da8cde267019bba906e7298f6efa619ba7a86d
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