Sentence Similarity
sentence-transformers
Safetensors
qwen2
feature-extraction
text-embeddings-inference
Instructions to use nomic-ai/nomic-embed-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nomic-ai/nomic-embed-code with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nomic-ai/nomic-embed-code") 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
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# Nomic Embed Code: A State-of-the-Art Code Retriever
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`nomic-embed-code` is a state-of-the-art code embedding model that excels at code retrieval tasks:
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# Nomic Embed Code: A State-of-the-Art Code Retriever
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[Blog](https://www.nomic.ai/blog/posts/introducing-state-of-the-art-nomic-embed-code) | [Technical Report](https://arxiv.org/abs/2412.01007) | [AWS SageMaker](https://aws.amazon.com/marketplace/seller-profile?id=seller-tpqidcj54zawi) | [Atlas Embedding and Unstructured Data Analytics Platform](https://atlas.nomic.ai)
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`nomic-embed-code` is a state-of-the-art code embedding model that excels at code retrieval tasks:
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