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---
license: apache-2.0
---
# MindedWheeler
Embody_AI with car as Demo
<p align="center">
🌐 <a href="https://github.com/FreedomIntelligence/MindedWheeler" target="_blank">Website</a> • 🤗 <a href="" target="_blank">Model</a>
</p>
## 🌈 Update
* **[2024.02.23]** 🎉🎉🎉 MindedWheeler is published！🎉🎉🎉
## 🤖 Model Training Data
```
User：快速向左转
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).
## 🤖 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 🤗 [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 <type>:
- 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 请快速向前
```
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.
## 🥸 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}},
}
```
## 🤖 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. |