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") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:0e544c173d6ef47db60a453e41c85bd9cba4822d6a39f0fbf557d29e95009916
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size 470641600
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