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update readme
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README_en.md
46
README_en.md
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- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
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- [MiniCPM-V 2.0](#minicpm-v-20)
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- [Online Demo](#online-demo)
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- [Chat with Our Demo on Gradio](#chat-with-our-demo-on-gradio)
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- [Install](#install)
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- [Inference](#inference)
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- [Model Zoo](#model-zoo)
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- [Multi-turn Conversation](#multi-turn-conversation)
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- [Inference on Mac](#inference-on-mac)
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- [Deployment on Mobile Phone](#deployment-on-mobile-phone)
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- [WebUI Demo](#webui-demo)
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- [Inference with llama.cpp](#inference-with-llamacpp)
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- [Inference with vLLM](#inference-with-vllm)
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- [Fine-tuning](#fine-tuning)
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@@ -458,9 +457,30 @@ We deploy MiniCPM-V 2.0 on end devices. The demo video is the raw screen recordi
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| OmniLMM-12B | [Document](./omnilmm_en.md) |
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## Chat with Our Demo on Gradio
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We provide online and local demo powered by HuggingFace [Gradio](https://www.gradio.app/guides/quickstart), the most popular model deployment framework nowadays. It supports streaming outputs, progress bars, queuing, alerts, and other useful features.
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### Online Demo <!-- omit in toc -->
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Click here to try out the online demo of [MiniCPM-Llama3-V 2.5](https://huggingface.co/spaces/openbmb/MiniCPM-Llama3-V-2_5) | [MiniCPM-V 2.0](https://huggingface.co/spaces/openbmb/MiniCPM-V-2) on HuggingFace Spaces.
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### Local WebUI Demo <!-- omit in toc -->
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You can easily build your own local WebUI demo with Gradio use the following commands.
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```shell
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pip install -r requirements.txt
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```
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```shell
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# For NVIDIA GPUs, run:
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python web_demo_2.5.py --device cuda
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# For Mac with MPS (Apple silicon or AMD GPUs), run:
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PYTORCH_ENABLE_MPS_FALLBACK=1 python web_demo_2.5.py --device mps
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```
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## Online Demo
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Click here to try out the Demo of [MiniCPM-Llama3-V 2.5](https://huggingface.co/spaces/openbmb/MiniCPM-Llama3-V-2_5) | [MiniCPM-V 2.0](https://huggingface.co/spaces/openbmb/MiniCPM-V-2).
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## Install
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@@ -582,24 +602,6 @@ PYTORCH_ENABLE_MPS_FALLBACK=1 python test.py
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### Deployment on Mobile Phone
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MiniCPM-V 2.0 can be deployed on mobile phones with Android operating systems. 🚀 Click [here](https://github.com/OpenBMB/mlc-MiniCPM) to install apk. MiniCPM-Llama3-V 2.5 coming soon.
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### WebUI Demo
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<details>
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<summary>Click to see how to deploy WebUI demo on different devices </summary>
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```shell
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pip install -r requirements.txt
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```
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```shell
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# For NVIDIA GPUs, run:
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python web_demo_2.5.py --device cuda
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# For Mac with MPS (Apple silicon or AMD GPUs), run:
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PYTORCH_ENABLE_MPS_FALLBACK=1 python web_demo_2.5.py --device mps
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```
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</details>
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### Inference with llama.cpp<a id="inference-with-llamacpp"></a>
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MiniCPM-Llama3-V 2.5 can run with llama.cpp now! See our fork of [llama.cpp](https://github.com/OpenBMB/llama.cpp/tree/minicpm-v2.5/examples/minicpmv) for more detail. This implementation supports smooth inference of 6~8 token/s on mobile phones (test environment:Xiaomi 14 pro + Snapdragon 8 Gen 3).
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