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README.md
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license: apache-2.0
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---
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license: apache-2.0
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---
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# EmbodyAICar
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Embody_AI with car as Demo
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<center>
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<img src="https://github.com/FreedomIntelligence/EmbodyAICar/blob/main/assets/embodyaicar.png" width="450" style="display: inline-block; vertical-align: top;"/>
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</center>
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<p align="center">
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🌐 <a href="" target="_blank">Website</a> • 🤗 <a href="" target="_blank">Model</a>
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</p>
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## 🌈 Update
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* **[2024.02.23]** 🎉🎉🎉 EmbodyAICar is published!🎉🎉🎉
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## 🤖 Model Training Data
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```
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User:快速向左转
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RobotAI: (1.0, -0.3)
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...
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```
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- The two float are in range [-1,1]
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- The first float is speed, the second is direction (negative means left, positive means right).
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## 🤖 Communication Protocol
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- 0x02, 0x02, 0x01, 8, data_buf; (See detail in [code](https://github.com/FreedomIntelligence/EmbodyAICar/blob/main/qwen.cpp#L151))
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## ℹ️ Usage
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1. DownLoad [Model]() and Follow [Qwen.cpp](https://github.com/QwenLM/qwen.cpp.git) get model.bin and qwen.tiktoken.
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2. Install package serial.tar.gz
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```
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cd serial
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cmake .. & make & sudo make install
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```
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3. Compile the project using CMake:
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```
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cmake -B build
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cmake --build build -j --config Release
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```
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4. Now you may chat and control your AI car with the quantized RobotAI model by running:
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```
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./build/bin/main -m robot1_8b-ggml.bin --tiktoken qwen.tiktoken -p 请快速向前
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```
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To run the model in interactive mode, add the -i flag. For example:
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```
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./build/bin/main -m robot1_8b-ggml.bin --tiktoken qwen.tiktoken -i
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```
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In interactive mode, your chat history will serve as the context for the next-round conversation.
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## 🥸 To do list
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- Continue to create data and train a robust model
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- Add ASR and TTS
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- ...
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## ✨ Citation
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Please use the following citation if you intend to use our dataset for training or evaluation:
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```
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@misc{embodyAiCar,
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title={EmbodyAICar: Embody_AI with car as Demo},
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author={Xidong Wang*, Yuan Shen*},
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year = {2024},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/FreedomIntelligence/EmbodyAICar}},
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}
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```
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## 🤖 Acknowledgement
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- We thank [Qwen.cpp](https://github.com/QwenLM/qwen.cpp.git) and [llama.cpp](https://github.com/ggerganov/llama.cpp) for their excellent work.
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