---
license: other
license_name: qwen-license
license_link: https://github.com/QwenLM/Qwen/blob/main/LICENSE
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
model_creator: erikmiller
model_name: Qwen2.5-Coder-7B-Swift-Lm
tags:
- swift
- swift6
- ios
- macos
- code
- qwen-2.5
- gguf
- ollie
- clawfi
language:
- en
library_name: transformers
pipeline_tag: text-generation
---

## Model Summary
Qwen2.5-Coder-7B-Swift-Lm is a fine-tuned version of the Qwen2.5-Coder-7B-Instruct model, specifically optimized for high-performance Swift development.

## Key Features
Modern Swift Proficiency: Deeply familiar with Swift 6 Concurrency (Actors, Sendable) and the Observation framework (@Observable).

Native SDK Knowledge: Fine-tuned to understand the nuances of SwiftUI, AppKit, and Combine.

Local Performance: Optimized for GGUF format to ensure low-latency inference on Apple Silicon (Metal) via tools like LM Studio.

## Training Details
Dataset: 5,602 high-quality, curated Swift examples.

Fine-tuning Method: QLoRA (Rank=16, Alpha=32).

Target Modules: q_proj, v_proj.

Objective: Improving code generation accuracy and reducing common pitfalls like forced-unwrapping.

## Training Results

Final Training Loss: 0.369

Training Epochs: 1

Loss Curve: The model showed a steady, controlled descent from an initial loss of 12.45 down to 0.36, indicating successful convergence on the Swift-specific dataset without aggressive overfitting.

## Usage Instructions
LM Studio / GGUF
Download the .gguf file from the Files and versions tab.

In LM Studio, load the model and enable GPU Offload to Max.

Set your system prompt to: "You are a Senior iOS Architect specializing in clean, safe, and modern Swift code."

Connecting to Cursor
Start the Local Server in LM Studio (default: http://localhost:1234).

In Cursor Settings, add a custom OpenAI API with the URL http://localhost:1234/v1.

Select this model to get fine-tuned Swift suggestions directly in your project.