amkyawdev/amk-coder-v2
amkyawdev/amk-coder-v2 is a 1.5 billion parameter language model fine-tuned from Qwen/Qwen2.5-Coder-1.5B, specifically optimized for code generation and coding assistance within a Myanmar language context. Developed by amkyawdev, this model leverages LoRA (PEFT) fine-tuning to provide localized support for programming tasks. With a context length of 32768 tokens, it is designed to understand and generate code based on Myanmar language instructions, making it suitable for building specialized coding assistants.
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Model Overview
amkyawdev/amk-coder-v2 is a 1.5 billion parameter language model, fine-tuned by amkyawdev from the Qwen/Qwen2.5-Coder-1.5B base model. Its primary distinction lies in its Myanmar-localized coding agent capabilities, making it unique among code generation models. The model was fine-tuned using LoRA (PEFT) with FP16 mixed precision on a custom Myanmar localized coding agent dataset.
Key Capabilities
- Myanmar Language Code Generation: Excels at generating code from instructions provided in the Myanmar language.
- Coding Assistance: Designed to act as a coding agent, providing support for various programming tasks.
- Qwen2.5-Coder Architecture: Benefits from the robust architecture of the Qwen2.5-Coder series, adapted for localized use.
- Tool Access Integration: Utilizes a ChatML structure that supports tool access, as demonstrated in its prompt format for expert Myanmar AI coding agents.
Good for
- Localized Coding Tools: Ideal for developing coding assistants and tools that cater to Myanmar-speaking developers.
- Instruction-Tuned Code Generation: Suitable for tasks requiring code generation based on specific instructions, particularly in a bilingual (Myanmar/English) context.
- Research and Development: Useful for exploring localized LLM applications in programming and natural language processing.
Limitations
- Not intended for production deployment without further fine-tuning or rigorous testing.
- May generate syntactically incorrect code or not adhere to security best practices.
- Myanmar language support, while a focus, may still have limitations compared to English.