Instructions to use nomic-ai/CodeRankEmbed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nomic-ai/CodeRankEmbed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nomic-ai/CodeRankEmbed", trust_remote_code=True) 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] - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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| Name | Parameters | CSN | CoIR |
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| :-------------------------------:| :----- | :-------- | :------: |
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| **CodeRankEmbed** | 137M | **77.9** |**60.1** |
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| CodeSage-Large | 1.3B | 71.2 | 59.4 |
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| Jina-Code-v2 | 161M | 67.2 | 58.4 |
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| CodeT5+ | 110M | 74.2 | 45.9 |
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| Voyage-Code-002 | Unknown | 68.5 | 56.3 |
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| Name | Parameters | CSN | CoIR |
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| :-------------------------------:| :----- | :-------- | :------: |
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| **CodeRankEmbed** | 137M | **77.9** |**60.1** |
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| Arctic-Embed-M-Long | 137M | 53.4 | 43.0 |
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| CodeSage-Small | 130M | 64.9 | 54.4 |
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| CodeSage-Base | 356M | 68.7 | 57.5 |
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| CodeSage-Large | 1.3B | 71.2 | 59.4 |
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| Jina-Code-v2 | 161M | 67.2 | 58.4 |
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| CodeT5+ | 110M | 74.2 | 45.9 |
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| OpenAI-Ada-002 | 110M | 71.3 | 45.6 |
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| Voyage-Code-002 | Unknown | 68.5 | 56.3 |
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