aasim-m/daft-qwen2.5-coder-7b-instruct-checkpoint-2000
The aasim-m/daft-qwen2.5-coder-7b-instruct-checkpoint-2000 is an intermediate 7.6 billion parameter checkpoint of a Qwen2.5-Coder-7B-Instruct model, fine-tuned by aasim-m for translating NVIDIA GPU assembly to AMD GPU assembly. This model is part of an ongoing supervised fine-tuning process, specifically optimized for code translation tasks between different GPU architectures. It leverages a 32,768 token context window and is intended for specialized code generation and translation within the GPU assembly domain.
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Overview
This model, aasim-m/daft-qwen2.5-coder-7b-instruct-checkpoint-2000, is an intermediate checkpoint from an ongoing supervised fine-tuning (SFT) process. It is based on the Qwen/Qwen2.5-Coder-7B-Instruct model and has been specifically trained to translate NVIDIA GPU assembly code into AMD GPU assembly code. This checkpoint represents 2,000 optimizer steps out of a planned 10,219, having processed all 163,495 eligible training pairs from the ahmedheakl/daft-sm89-rdna-functions dataset.
Key Capabilities
- Specialized Code Translation: Primarily designed for translating NVIDIA GPU assembly functions to AMD GPU assembly, preserving original behavior.
- Intermediate Checkpoint: This is not the final model but an ongoing development, indicating potential for further refinement and improved performance.
- Large Context Window: Utilizes a 32,768 token context for both prompt and response, beneficial for handling complex assembly code snippets.
Good for
- GPU Assembly Development: Researchers and developers working on cross-architecture GPU code migration or optimization.
- Experimentation: Ideal for those interested in evaluating the progress of a specialized code translation model at an intermediate stage.
- Understanding Code Translation: Provides a foundation for exploring how large language models can be fine-tuned for highly specific, technical code transformation tasks.