ESHMO-AI/Llama_Coder
ESHMO-AI/Llama_Coder is a 34 billion parameter instruction-tuned generative text model based on Meta's Code Llama architecture, designed for general code synthesis and understanding. This model is specifically optimized for following instructions and chat-based code assistance. It supports code completion and is intended for commercial and research use in English and relevant programming languages. The model is an auto-regressive language model utilizing an optimized transformer architecture.
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ESHMO-AI/Llama_Coder: Instruction-Tuned Code Generation
This model is the 34 billion parameter instruction-tuned variant of Meta's Code Llama family, an auto-regressive language model built on an optimized transformer architecture. It is specifically designed for general code synthesis and understanding, with a focus on instruction following and chat-based interactions.
Key Capabilities
- Code Completion: Generates code snippets and completes existing code.
- Instruction Following / Chat: Responds to natural language instructions for code-related tasks.
- General Code Synthesis: Capable of generating various types of code.
Good For
- Code Assistant Applications: Ideal for building tools that help developers with coding tasks.
- Research and Commercial Use: Suitable for both academic research and commercial deployment in English and programming languages.
- Instruction-Based Code Generation: Excels when provided with clear instructions for desired code output.
This model is a static release, trained between January and July 2023, and is governed by a custom commercial license from Meta. More details can be found in the research paper.