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Updated README.md with correct links to deployment documentation on llama.cpp #69

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6 changes: 3 additions & 3 deletions README.md
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Expand Up @@ -53,7 +53,7 @@ MobileVLM: Vision Language Model for Mobile Devices
* **`Feb. 26th, 2024`**: MobileVLM V2 training data and code are available now! Follow the instructions below to train your own mobileVLM V2 model !
* **`Feb. 06th, 2024`**: 🔥🔥🔥 **MobileVLM V2** is out! Paper [here](https://arxiv.org/abs/2402.03766)! The inference code of MobileVLM V2 is available now! Our MobileVLM V2 weights are publicly available on the HuggingFace website. Enjoy [them](https://huggingface.co/mtgv/) !
* **`Feb. 06th, 2024`**: The SFT code and dataset of MobileLLaMA are released now! You can train your own chat model.
* **`Jan. 23rd, 2024`**: 🚀🚀🚀 **MobileVLM** is officially supported by [`llama.cpp`](https://github.com/ggerganov/llama.cpp/blob/master/examples/llava/MobileVLM-README.md) now ! Have a try !
* **`Jan. 23rd, 2024`**: 🚀🚀🚀 **MobileVLM** is officially supported by [`llama.cpp`](https://github.com/ggml-org/llama.cpp/blob/master/examples/llava/MobileVLM-README.md) now ! Have a try !
* **`Jan. 15th, 2024`**: Customized `llama.cpp` for **MobileVLM** and its [deployment instruction](#deployment-on-mobile-devices) on mobile devices.
* **`Jan. 11st, 2024`**: The training and evaluation codes of MobileVLM are available now! Follow these step-by-step instructions below to easily train your own mobileVLM in **5 hours** ⚡️ !
* **`Dec. 31st, 2023`**: Our MobileVLM weights are uploaded on the HuggingFace website. We also provide inference examples for the MobileLLaMA/MobileVLM model so that anyone can enjoy [them](https://huggingface.co/mtgv/) early.
Expand Down Expand Up @@ -315,12 +315,12 @@ Note: You may skip MobileLLaMA training processes and directly start with Mobile

## <h2 id="deployment-on-mobile-devices">📲 Deployment on Mobile Devices </h2>
**MobileVLM** now is officially supported by `llama.cpp`. We are looking for more cooperation with open-source communities on the deployment of mobile devices.
- [llama.cpp](https://github.com/ggerganov/llama.cpp): the repository of official `llama.cpp`. Step-by-step deployment instructions are provided [here](https://github.com/ggerganov/llama.cpp/blob/master/examples/llava/MobileVLM-README.md).
- [llama.cpp](https://github.com/ggml-org/llama.cpp): the repository of official `llama.cpp`. Step-by-step deployment instructions are provided [here](https://github.com/ggml-org/llama.cpp/blob/master/docs/multimodal/MobileVLM.md).
## 🤝 Acknowledgments

- [LLaVA](https://github.com/haotian-liu/LLaVA): the codebase we built upon. Thanks for their wonderful work! 👏
- [Vicuna](https://github.com/lm-sys/FastChat): the amazing open-sourced large language model!
- [llama.cpp](https://github.com/ggerganov/llama.cpp): the great open-sourced framework for the inference of LLaMA model in pure C/C++!
- [llama.cpp](https://github.com/ggml-org/llama.cpp): the great open-sourced framework for the inference of LLaMA model in pure C/C++!


## ✏️ Reference
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