Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
mathematics
scientific-papers
retrieval
matryoshka
text-embeddings-inference
Instructions to use RobBobin/math-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RobBobin/math-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RobBobin/math-embed") 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
- Xet hash:
- 07682b0ea1663f49615bd3ca45087c00b73a728f314cb725eb4bed3954ef9f37
- Size of remote file:
- 440 MB
- SHA256:
- 4f49fba1357a7193677791c2ef52d8b989d5ce0f438dd8b7523b3790da99e6d8
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