metadata
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-de1
A Delphi/ObjectPascal coding assistant built on deepseek-coder-6.7b-instruct.
13-line FATPIE system prompt, 4096 context. Proven 127/136 on smoketest.
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
# Download the Modelfile
# Then create the model:
ollama create deepseek-coder:6.7b-instruct-de1 -f Modelfile.de1
# Run it:
ollama run deepseek-coder:6.7b-instruct-de1 "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
- 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
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.