Sentence Similarity
sentence-transformers
ONNX
English
code
nomic_bert
code-search
embeddings
cqs
custom_code
text-embeddings-inference
Instructions to use jamie8johnson/CodeRankEmbed-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jamie8johnson/CodeRankEmbed-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jamie8johnson/CodeRankEmbed-onnx", trust_remote_code=True) 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:
- 941de96706347c4d9d874be26e64b88f11ac03313b0f849317da71da19ae785d
- Size of remote file:
- 548 MB
- SHA256:
- a5454ae55b5ee6888b8f59f30c645c9da1c6ac887627b84dc62b30064bce9546
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