--- license: other license_name: deepseek base_model: deepseek-ai/deepseek-coder-6.7b-instruct tags: - delphi - objectpascal - code-assistant - system-prompt language: - en --- # deepseek-coder-6.7b-instruct-de2 **A Delphi/ObjectPascal coding assistant built on deepseek-coder-6.7b-instruct.** 100-item comprehensive system prompt, 8192 context. Experimental. ## What is this? This is **not a fine-tuned model**. It uses the unmodified deepseek-coder-6.7b-instruct weights with a carefully crafted system prompt that activates the model's existing knowledge of Delphi/ObjectPascal conventions. Six QLoRA fine-tuning attempts on this base model either had zero effect or caused regression. The system prompt alone produces better results than any fine-tuned variant. ## How to use ### With Ollama ```bash # Download the Modelfile # Then create the model: ollama create deepseek-coder:6.7b-instruct-de2 -f Modelfile.de2 # Run it: ollama run deepseek-coder:6.7b-instruct-de2 "Write a Delphi function that reverses a string" ``` ### What the system prompt teaches - **Memory management**: No ARC or GC on Windows. Free every object you create. - **FATPIE naming**: T for types, F for fields, A for parameters, P for pointers, I for interfaces, E for exceptions - **Code style**: Use Result not FunctionName, begin not BEGIN, try/finally for cleanup - **Platform**: Delphi on Windows, MSBuild for builds, TDateTime for dates ## Model details - **Base model**: [deepseek-ai/deepseek-coder-6.7b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) - **Weights**: Unmodified — no LoRA, no fine-tuning - **Method**: System prompt engineering only - **Author**: Warren Postma (warren.postma@gmail.com) - **Project**: [WARP — local AI agent for Delphi/ObjectPascal](https://github.com/wpostma) ## Key finding > A well-crafted system prompt on an unmodified 6.7B model beats QLoRA fine-tuning > with 500-1000 curated instruction pairs. The model already knows Delphi — it just > needs the right context to access that knowledge.