--- license: apache-2.0 --- # MindedWheeler Embody_AI with car as Demo ![MindedWheeler](assets/MindedWheeler.png)

🌐 Website β€’ πŸ€— Model

## 🌈 Update * **[2024.02.23]** πŸŽ‰πŸŽ‰πŸŽ‰ MindedWheeler is publishedοΌπŸŽ‰πŸŽ‰πŸŽ‰ ## πŸ€– Model Training Data ``` UserοΌšεΏ«ι€Ÿε‘ε·¦θ½¬ RobotAI: (1.0, -0.3) ... ``` - The two float are in range [-1,1] - The first float is speed, the second is direction (negative means left, positive means right). ## πŸ€– Communication Protocol - 0x02, 0x02, 0x01, 8, data_buf; (See detail in [code](https://github.com/FreedomIntelligence/MindedWheeler/blob/main/qwen.cpp#L151)) ## ℹ️ Usage 1. DownLoad πŸ€— [Model](https://huggingface.co/FreedomIntelligence/MindedWheeler) get model.bin. ``` cd MindedWheeler git submodule update --init --recursive python qwen_cpp/convert.py -i {Model_Path} -t {type} -o robot1_8b-ggml.bin ``` You are free to try any of the below quantization types by specifying -t : - q4_0: 4-bit integer quantization with fp16 scales. - q4_1: 4-bit integer quantization with fp16 scales and minimum values. - q5_0: 5-bit integer quantization with fp16 scales. - q5_1: 5-bit integer quantization with fp16 scales and minimum values. - q8_0: 8-bit integer quantization with fp16 scales. - f16: half precision floating point weights without quantization. - f32: single precision floating point weights without quantization. 2. Install package serial.tar.gz ``` cd serial cmake .. & make & sudo make install ``` 3. Compile the project using CMake: ``` cmake -B build cmake --build build -j --config Release ``` 4. Now you may chat and control your AI car with the quantized RobotAI model by running: - qwen.tiktoken is in the model directory ``` ./build/bin/main -m robot1_8b-ggml.bin --tiktoken qwen.tiktoken -p θ―·εΏ«ι€Ÿε‘ε‰ ``` To run the model in interactive mode, add the -i flag. For example: ``` ./build/bin/main -m robot1_8b-ggml.bin --tiktoken qwen.tiktoken -i ``` In interactive mode, your chat history will serve as the context for the next-round conversation. ## πŸ₯Έ To do list - Continue to create data and train a robust model - Add ASR and TTS - ... ## ✨ Citation Please use the following citation if you intend to use our dataset for training or evaluation: ``` @misc{MindedWheeler, title={MindedWheeler: Embody_AI with car as Demo}, author={Xidong Wang*, Yuan Shen*}, year = {2024}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/FreedomIntelligence/MindedWheeler}}, } ``` ## πŸ€– Acknowledgement - We thank [Qwen.cpp](https://github.com/QwenLM/qwen.cpp.git) and [llama.cpp](https://github.com/ggerganov/llama.cpp) for their excellent work.