ai-lqm/ai-localqmod-js-slm

AI LocalQmod — JS-family Code SLMs (GGUF)

Ultra-small, single-purpose code-generation models — as light as ~17 MB.

This repository hosts a family of small language models (SLMs) trained from scratch specifically for JavaScript-ecosystem code generation. They are built and distributed by AI LocalQmod for use with AI-App Builder, a local-first AI app generation tool, but the GGUF files are plain llama.cpp models and can be loaded with any GGUF-compatible runtime (llama.cpp, llama-cpp-python, Ollama with a Modelfile, LM Studio, etc.).

Unlike general-purpose LLMs, each model here is trained on a narrow, single-purpose corpus (natural-language instruction → JS-family code) with a from-scratch tokenizer tuned for that language's syntax and vocabulary. This trades general reasoning ability for extremely small size and fast local inference, making them a good fit for lightweight, single-purpose code-completion helpers rather than full coding assistants.

Models

File	Target	Quantization	Size
js-slm-Q4_K_M-chat.gguf	JavaScript	Q4_K_M	17.7 MB
jsts-slm-Q4_K_M-chat.gguf	JavaScript + TypeScript	Q4_K_M	17.5 MB
node-slm-Q4_K_M-chat.gguf	Node.js (fs/path/process/http/events)	Q4_K_M	20.0 MB
react-slm-Q4_K_M-chat.gguf	React components	Q4_K_M	16.6 MB
js-loops-slm-Q4_K_M-chat.gguf	JavaScript (for-loops + arrays: sum/max/count/filter/map/average)	Q4_K_M	20.4 MB

Sizes measured with stat -f%z (exact byte count), not rounded ls -lh output.

Intended use

• Local, single-purpose code generation for the target language/framework shown above
• Multi-agent "orchestration" pipelines where a larger LLM plans and one of these SLMs generates individual small functions/components
• Environments where downloading a multi-GB model is impractical (offline demos, low-disk devices, quick experiments)

Not intended for

• General-purpose chat or reasoning
• Large, multi-file refactors or architecture design
• Languages/frameworks outside each model's specific target (see table above)

Usage (llama.cpp)

llama-cli -m js-slm-Q4_K_M-chat.gguf -p "Write a function that returns the sum of an array" -n 128

Usage (llama-cpp-python)

from llama_cpp import Llama

llm = Llama(model_path="js-slm-Q4_K_M-chat.gguf")
result = llm.create_chat_completion(
    messages=[{"role": "user", "content": "Write a function that returns the sum of an array"}]
)
print(result["choices"][0]["message"]["content"])

License

MIT. Free to use, modify, and redistribute.

About AI LocalQmod

AI LocalQmod builds local-first, privacy-respecting AI tools. Learn more at ai-localqmod.com.