LaboAI-0.3.3-1.5B
This is a lightweight language model (1.5B parameters) fine-tuned specifically for generating, understanding, and debugging Kotlin code and Android development (with a strong emphasis on Jetpack Compose, Coroutines, and modern architectures).
This version (0.3.3) is the result of an optimized, multi-dataset training regimen designed for extreme efficiency. It is optimized using QLoRA (4-bit) to run locally on GPUs with limited VRAM (such as the NVIDIA Quadro M2000 with 4GB) without sacrificing code quality.
📋 Model Details
- Developed by: Mmxa
- Organization: LaboAI
- Model type: Causal Language Model (Code Generation)
- Languages: Kotlin, Java, English, Spanish (instructions)
- License: Apache 2.0 (inherited from Qwen2.5)
- Base model: Qwen/Qwen2.5-1.5B-Instruct
🚀 Uses
Direct Use
- Generating boilerplate for Activities, Fragments, ViewModels, and Repositories in Kotlin.
- Creating modern UI components with Jetpack Compose.
- Debugging compilation errors or logic flaws in Android code snippets.
- Translating legacy Java logic into modern, idiomatic Kotlin.
Ecosystem Use (Recommended)
This model shines when used as a local coding assistant via Ollama and the Continue extension in VS Code. This guarantees complete privacy (your code never leaves your machine) and ultra-low latency.
Out-of-Scope Uses
- It is not optimized for general chat, creative writing, or complex mathematical reasoning.
- It should not be used to generate malicious code or exploits.
- All generated code must be reviewed by a human developer before being merged into a main branch.
️ Limitations and Risks
- API Hallucinations: In rare cases, it might suggest deprecated Android APIs instead of modern alternatives.
- Context Window: Optimized for 1024-2048 tokens. It is not suitable for analyzing massive, multi-thousand-line codebase files all at once.
- Dependencies: It does not have real-time knowledge of the latest Android library updates.
💻 How to Get Started (Local Setup)
This repository includes both the original format (safetensors) and the quantized format (GGUF Q4_K_M). To use it on your PC with a 4GB VRAM GPU:
- Install Ollama.
- Download the
.gguffile from this repository (e.g.,LaboAI-0.3.3-1.5B-Q4_K_M.gguf). - Create a file named
Modelfilein the same folder with the following content:FROM ./LaboAI-0.3.3-1.5B-Q4_K_M.gguf PARAMETER stop "### Instruction:" PARAMETER stop "### Response:"