Instructions to use XiweiZ/sts-ft-promptInjection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use XiweiZ/sts-ft-promptInjection with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("XiweiZ/sts-ft-promptInjection") 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-promptInjection with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("XiweiZ/sts-ft-promptInjection") 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-promptInjection: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/XiweiZ/sts-ft-promptInjection/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://XiweiZ/sts-ft-promptInjection/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/XiweiZ/sts-ft-promptInjection/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- f54b19fc5c2885b34f7c81f8ecf4caffe8018e29b5b6d84470dd4f37561d0a12
- Size of remote file:
- 438 MB
- SHA256:
- 45496c68bd7c7cfc85678bdaeeb9c6676f6420b2629875e9db0ddea0b8101fac
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