Instructions to use sentence-transformers/average_word_embeddings_levy_dependency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/average_word_embeddings_levy_dependency with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/average_word_embeddings_levy_dependency") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (0c0abb68cfd979c0122836b0651fb06fbe5bff94) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>d074985
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Remove deprecated (SEB) evaluation results section
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Update Sentence Transformers metadata (#1)
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Update README.md
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Add new SentenceTransformer model.
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initial commit
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