Qodo Embed -1-7B is an open-source code embedding model developed for high-performance code understanding, search, and retrieval-augmented generation (RAG) tasks. It is a 7-billion parameter transformer model optimized for producing high-quality vector embeddings of code across multiple programming languages.

Features of Qodo Embed -1-7B:

High-performance transformer model designed specifically for code embedding and retrieval use cases.
Open-weight model released under the Apache 2.0 license.
Supports multi-language code understanding and semantic search applications.
Integrates with libraries like SentenceTransformers and Hugging Face Transformers for easy deployment.
Optimized for RAG pipelines and similarity search in codebases or developer tools.
Can be deployed locally or in the cloud for scalable embedding tasks.

To check the installed version of Qodo Embed -1-7B (if using it via Hugging Face Transformers), use the following commands:

$ pip show sentence-transformers
$ pip show transformers

Disclaimer: Qodo Embed -1-7B is open-source software provided under the Apache 2.0 License by Qodo.ai. It is intended for research and development purposes. For accurate usage, updates, and limitations, refer to the official documentation. The authors and contributors are not liable for any outcomes resulting from its use. Use responsibly.

Qodo embed -1-7bbCloud LLC

Qodo embed -1-7b

bCloud LLC

Qodo embed -1-7b

bCloud LLC

Qodo embed -1-7b
bCloud LLC