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:
- 4ce0e9701f65956de9bbc184aa64d4c5a577c39c01234889cbcf33744a8ed487
- Size of remote file:
- 434 kB
- SHA256:
- 37f101af6add9127f6bdca0936e975aeb45a082d4cd656d5b35d1803389b30a9
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