ramgpt 13b Coding Model (LLM PoC) Description
Overview
This document provides an overview of the ramgpt 13b coding model, which is based on the CodeLlama architecture and is designed to work seamlessly with the ramgpt inferencing platform.
Model Specifications
Base Architecture
- Architecture: CodeLlama
- Model Size: 13 billion parameters
Integration
- Platform Compatibility: Compatible with ramgpt inferencing platform for efficient and scalable deployment.
Features
- Advanced Coding Capabilities: The model excels in understanding and generating complex code structures, making it ideal for a wide range of programming tasks.
- High Adaptability: Designed to quickly adapt to new coding patterns and languages, ensuring its utility in diverse development environments.
- Optimized for Efficiency: The model's architecture is optimized for high-performance inferencing, offering fast response times even for complex coding queries.
Use Cases
- Automated Code Generation: Assists in writing code by automatically generating code snippets based on user input.
- Code Review and Analysis: Capable of analyzing existing code for potential improvements or issues.
- Language Translation: Translates code between various programming languages.
Getting Started
To start using the 13b coding model with the ramgpt inferencing platform, follow these steps:
- Setup: Ensure that the ramgpt inferencing platform is properly set up and running.
- Model Deployment: Deploy the 13b coding model onto the platform.
- Integration: Integrate the model with your development environment or workflow.
Support and Contribution
For support or to contribute to the development of this model, please visit the GitHub repository or contact our development team.
Note: This model is continuously updated to incorporate the latest advancements in AI and programming language syntax and semantics.
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