Shirdel-Coder is a code-specialized language model optimized for local inference and software development workflows. The model is designed to provide strong performance across programming and code generation tasks while maintaining efficient execution on consumer hardware.

The model was fine-tuned using Claude Fable 5–style instruction supervision together with the Evol-Instruct-Code-80k-v1 dataset to improve coding capabilities, instruction following, and structured reasoning during software development tasks. After training, the model was converted to GGUF format and quantized using Q6_K to balance quality, memory efficiency, and inference speed for local deployment through Ollama.

Shirdel-Coder is intended for developers seeking a locally deployable coding assistant that can support multiple stages of the development cycle, from writing and completing code to debugging, refactoring, and explaining implementation details. The model is suitable for personal workstations, local AI environments, and privacy-focused development setups where running models without cloud dependency is preferred.

Optimizations focus on maintaining practical coding performance while reducing hardware requirements, making the model usable across a broad range of systems that support GGUF inference.

Features

Optimized for local inference with efficient memory usage

GGUF Q6_K quantization for a balance of quality and speed

Fine-tuned with Claude Fable 5–style instruction supervision

Trained with Evol-Instruct-Code-80k-v1 coding instruction data

Supports code generation across multiple programming languages

Code completion and inline code suggestion

Debugging assistance and error analysis

Refactoring and code improvement recommendations

Code explanation and documentation generation

Structured instruction following for development tasks

Supports algorithm design and problem solving

Assists with API usage and software implementation patterns

Suitable for privacy-focused and offline development environments

Compatible with local deployment using Ollama

Typical Use Cases

Generate complete functions and scripts

Explain existing codebases

Detect and fix programming errors

Refactor legacy code

Create boilerplate and project structures

Generate comments and documentation

Assist with learning programming concepts

Support rapid prototyping and software development workflows

Recommended Tasks

Python

JavaScript / TypeScript

C / C++

Java

Go

Rust

HTML / CSS

Shell scripting

SQL

General software engineering tasks