| Property | Value |
|---|---|
| Parameter Count | 161M |
| License | Apache 2.0 |
| Sequence Length | 8192 tokens |
| Technical Paper | arXiv:2310.19923 |
| Tensor Type | FP16 |
What is jina-embeddings-v2-base-code?
Jina-embeddings-v2-base-code is an advanced multilingual embedding model specifically designed for code understanding and processing. Built on a BERT architecture with symmetric bidirectional ALiBi, it supports both English and 30 programming languages, making it particularly valuable for technical documentation and code search applications.
Implementation Details
The model is built upon the JinaBert architecture and was pretrained on the github-code dataset, followed by training on over 150 million carefully curated coding question-answer and docstring pairs. While trained at 512 sequence length, it can handle up to 8192 tokens thanks to ALiBi positioning.
- Utilizes mean pooling for optimal embedding generation
- Supports integration with both PyTorch and Transformers.js
- Built-in support for sentence-transformers framework
- High-performance inference with FP16 precision
Core Capabilities
- Multilingual code understanding across 30+ programming languages
- Extended context window of 8192 tokens
- Efficient processing with 161M parameters
- Specialized for technical Q&A and code search
- Support for major programming languages including Python, JavaScript, Java, C++, and more
Frequently Asked Questions
Q: What makes this model unique?
The model's combination of extensive programming language support, long sequence handling capability (8192 tokens), and specialized training on code-related content sets it apart. The implementation of ALiBi positioning enables effective processing of longer sequences without performance degradation.
Q: What are the recommended use cases?
The model excels in code search applications, technical documentation processing, programming Q&A systems, and code similarity analysis. It's particularly effective for applications requiring understanding of multiple programming languages and long code sequences.