--- library_name: rkllm pipeline_tag: text-generation license: other license_name: qwen-research license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct/blob/main/LICENSE base_model: - Qwen/Qwen2.5-Coder-3B-Instruct tags: - text-generation-inference - rkllm - rk3588 - rockchip - edge-ai - qwen2 - code - chat --- # Qwen2.5-Coder-3B-Instruct — RKLLM build for RK3588 boards ### Built with Qwen **Author:** @jamescallander **Source model:** [Qwen/Qwen2.5-Coder-3B-Instruct · Hugging Face](https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct) **Target:** Rockchip RK3588 NPU via **RKNN-LLM Runtime** > This repository hosts a **conversion** of `Qwen2.5-Coder-3B-Instruct` for use on Rockchip RK3588 single-board computers (Orange Pi 5 plus, Radxa Rock 5b+, Banana Pi M7, etc.). Conversion was performed using the [RKNN-LLM toolkit](https://github.com/airockchip/rknn-llm?utm_source=chatgpt.com) #### Conversion details - RKLLM-Toolkit version: v1.2.1 - NPU driver: v0.9.8 - Python: 3.12 - Quantization: `w8a8_g128` - Output: single-file `.rkllm` artifact - Modifications: quantization (w8a8_g128), export to .rkllm format for RK3588 SBCs. - Tokenizer: not required at runtime (UI handles prompt I/O) ## ⚠️ Code generation disclaimer 🛑 **This model may produce incorrect, insecure, or non-optimal code.** - It is intended for **research, educational, and prototyping purposes only**. - Always **review, test, and validate** any generated code before using it in production. - The model does not guarantee compliance with security best practices or coding standards. - You are responsible for ensuring outputs meet your project’s requirements and legal obligations. ## Intended use - On-device deployment of a **coding-focused instruction model** for software development assistance on SBCs. - Qwen2.5-Coder-3B-Instruct is tuned for **code generation, explanation, and debugging tasks**, making it suitable for private edge inference. ## Limitations - Requires 4GB free memory - Quantized build (`w8a8_g128`) may show small quality differences vs. full-precision upstream. - Tested on a Radxa Rock 5B+; other devices may require different drivers/toolkit versions. ## Quick start (RK3588) ### 1) Install runtime The RKNN-LLM toolkit and instructions can be found on the specific development board's manufacturer website or from [airockchip's github page](https://github.com/airockchip). Download and install the required packages as per the toolkit's instructions. ### 2) Simple Flask server deployment The simplest way the deploy the `.rkllm` converted model is using an example script provided in the toolkit in this directory: `rknn-llm/examples/rkllm_server_demo` ```bash python3 /rknn-llm/examples/rkllm_server_demo/flask_server.py \ --rkllm_model_path /Qwen2.5-Coder-3B-Instruct_w8a8_g128_rk3588.rkllm \ --target_platform rk3588 ``` ### 3) Sending a request A basic format for message request is: ```json { "model":"Qwen2.5-Coder-3B", "messages":[{ "role":"user", "content":""}], "stream":false } ``` Example request using `curl`: ```bash curl -s -X POST :8080/rkllm_chat \ -H 'Content-Type: application/json' \ -d '{"model":"Qwen2.5-Coder-3B","messages":[{"role":"user","content":"Explain in one sentence what a static method is."}],"stream":false}' ``` The response is formated in the following way: ```json { "choices":[{ "finish_reason":"stop", "index":0, "logprobs":null, "message":{ "content":", "role":"assistant"}}], "created":null, "id":"rkllm_chat", "object":"rkllm_chat", "usage":{ "completion_tokens":null, "prompt_tokens":null, "total_tokens":null} } ``` Example response: ```json {"choices":[{"finish_reason":"stop","index":0,"logprobs":null,"message":{"content":"A static method belongs to the class itself rather than any instance of the class and can be called without creating an object of the class.","role":"assistant"}}],"created":null,"id":"rkllm_chat","object":"rkllm_chat","usage":{"completion_tokens":null,"prompt_tokens":null,"total_tokens":null}} ``` ### 4) UI compatibility This server exposes an **OpenAI-compatible Chat Completions API**. You can connect it to any OpenAI-compatible client or UI (for example: [Open WebUI](https://github.com/open-webui/open-webui?utm_source=chatgpt.com)) - Configure your client with the API base: `http://:8080` and use the endpoint: `/rkllm_chat` - Make sure the `model` field matches the converted model’s name, for example: ```json { "model": "Qwen2.5-Coder-3B-Instruct", "messages": [{"role":"user","content":"Hello!"}], "stream": false } ``` # License This conversion follows the license of the source model: [LICENSE · Qwen/Qwen2.5-Coder-3B-Instruct at main](https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct/blob/main/LICENSE)