Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,86 @@
+---
+license: mit
+language:
+- en
+- ja
+tags:
+- gguf
+- llama.cpp
+- code-generation
+- javascript
+- typescript
+- react
+- nodejs
+- slm
+pipeline_tag: text-generation
+---
+
+# 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](https://ai-localqmod.com), a local-first
+AI app generation tool, but the GGUF files are plain [llama.cpp](https://github.com/ggerganov/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)
+
+```bash
+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)
+
+```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](https://ai-localqmod.com).