CodeGen-2B-multi
| Property | Value |
|---|---|
| Parameters | 2 Billion |
| License | BSD-3-Clause |
| Author | Salesforce |
| Paper | View Research Paper |
What is codegen-2B-multi?
CodeGen-2B-multi is an advanced autoregressive language model specifically designed for program synthesis. Developed by Salesforce, this model represents a sophisticated approach to converting natural language descriptions into executable code. It's part of the larger CodeGen family and was trained on an impressive 119.2B tokens across multiple programming languages.
Implementation Details
The model implementation follows a carefully structured training approach, initially being initialized with CodeGen-NL 2B and then further pre-trained on the BigQuery dataset. The training process utilized TPU-v4-512 hardware from Google, incorporating both data and model parallelism techniques.
- Trained on multiple programming languages including C, C++, Go, Java, JavaScript, and Python
- Uses cross-entropy loss for training optimization
- Implements the transformers architecture for efficient processing
Core Capabilities
- Program synthesis from natural language descriptions
- Code completion and suggestion generation
- Multi-language code generation support
- Feature extraction from both natural language and programming language texts
Frequently Asked Questions
Q: What makes this model unique?
This model stands out due to its extensive training on multiple programming languages and its initialization from CodeGen-NL 2B, making it particularly effective at understanding and generating code across different programming paradigms.
Q: What are the recommended use cases?
The model is best suited for program synthesis tasks where natural language descriptions need to be converted into executable code. It excels at completing partially-generated code and can be effectively used for automated code generation when provided with English prompts in the form of comment strings.
