A 4B-parameter coding assistant for Python and TypeScript — runs entirely on-device, no code ever leaves your machine. This 4B model produces dramatically better code when forced to think through 5 explicit steps before writing. Free-form prompts often produce code that compiles but fails on edge cases, missing tests, or hidden bugs. Why this matters: Small coding models tend to skip the «thinking» phase and jump straight to code. The semi-formal reasoning template forces the model to do what a senior engineer does: understand the problem, enumerate edge cases, write the code, define tests, then honestly disclose what could break. 1. Problem Understanding — restate the requirement, identify ambiguities 2. Edge Cases and Constraints — enumerate what could go wrong before coding 3. Implementation — the actual code, with inline comments only where needed 4. Tests — concrete test cases covering happy path + edge cases 5. Known Limitations — what this code does NOT handle, dependencies, assumptions // Clean code. Comments only where the WHY is non-obvious. // Runnable tests covering edge cases above — Want code-only output (no explanation)? Replace OUTPUTFORMAT with: «Code blocks…
Модальности:
Генерация текста
Области применения:
Генерация кода Диалог / чат
Языки программирования:
Python TypeScript
Задача: Генерация текста
Автор: BrainboxAI
Теги: gguf, gemma4, image-text-to-text, code, python, typescript, coding-assistant, llama.cpp
Лайков: 4 | Загрузок: 180
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
