Instructions to use scroobiustrip/sov-model-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use scroobiustrip/sov-model-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("scroobiustrip/sov-model-v1") 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 scroobiustrip/sov-model-v1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("scroobiustrip/sov-model-v1") 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 scroobiustrip/sov-model-v1: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/scroobiustrip/sov-model-v1/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://scroobiustrip/sov-model-v1@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/scroobiustrip/sov-model-v1/resolve/refs%2Fpr%2F1/pytorch_model.bin
471 MB
- Xet hash:
- 73a103820f35da6276242d2ad913aa6f2970dde71755bc34989e47b26610ffc1
- Size of remote file:
- 471 MB
- SHA256:
- b6e3ef09a1791a9ccc157fe13545bd0e1fe45e34fdeb477bbdef5bb55ef2bbe1
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