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README.md
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@@ -53,8 +53,7 @@
- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25) - [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [MiniCPM-V 2.0](#minicpm-v-20) - [MiniCPM-V 2.0](#minicpm-v-20)
- [Online Demo](#online-demo) - [Chat with Our Demo on Gradio](#chat-with-our-demo-on-gradio)
- [Gradio-based Demo](#gradio-based-demo)
- [Install](#install) - [Install](#install)
- [Inference](#inference) - [Inference](#inference)
- [Model Zoo](#model-zoo) - [Model Zoo](#model-zoo)
@@ -458,14 +457,17 @@ We deploy MiniCPM-V 2.0 on end devices. The demo video is the raw screen recordi
| OmniLMM-12B | [Document](./omnilmm_en.md) | | OmniLMM-12B | [Document](./omnilmm_en.md) |
## Chat with Our Demo on Gradio
## Online Demo 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.
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).
## Gradio-based Demo ### Online Demo <!-- omit in toc -->
We supports buliding local WebUI demo with [Gradio](https://www.gradio.app/guides/quickstart), which inherently supports queuing, streaming outputs, alerts, progress_bars and other useful features! 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.
### Local WebUI Demo <!-- omit in toc -->
You can easily build your own local WebUI demo with Gradio use the following commands.
```shell ```shell
pip install -r requirements.txt pip install -r requirements.txt

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README_en.md
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@@ -53,14 +53,13 @@
- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25) - [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [MiniCPM-V 2.0](#minicpm-v-20) - [MiniCPM-V 2.0](#minicpm-v-20)
- [Online Demo](#online-demo) - [Chat with Our Demo on Gradio](#chat-with-our-demo-on-gradio)
- [Install](#install) - [Install](#install)
- [Inference](#inference) - [Inference](#inference)
- [Model Zoo](#model-zoo) - [Model Zoo](#model-zoo)
- [Multi-turn Conversation](#multi-turn-conversation) - [Multi-turn Conversation](#multi-turn-conversation)
- [Inference on Mac](#inference-on-mac) - [Inference on Mac](#inference-on-mac)
- [Deployment on Mobile Phone](#deployment-on-mobile-phone) - [Deployment on Mobile Phone](#deployment-on-mobile-phone)
- [WebUI Demo](#webui-demo)
- [Inference with llama.cpp](#inference-with-llamacpp) - [Inference with llama.cpp](#inference-with-llamacpp)
- [Inference with vLLM](#inference-with-vllm) - [Inference with vLLM](#inference-with-vllm)
- [Fine-tuning](#fine-tuning) - [Fine-tuning](#fine-tuning)
@@ -458,9 +457,30 @@ We deploy MiniCPM-V 2.0 on end devices. The demo video is the raw screen recordi
| OmniLMM-12B | [Document](./omnilmm_en.md) | | OmniLMM-12B | [Document](./omnilmm_en.md) |
## Chat with Our Demo on Gradio
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.
### Online Demo <!-- omit in toc -->
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.
### Local WebUI Demo <!-- omit in toc -->
You can easily build your own local WebUI demo with Gradio use the following commands.
```shell
pip install -r requirements.txt
```
```shell
# For NVIDIA GPUs, run:
python web_demo_2.5.py --device cuda
# For Mac with MPS (Apple silicon or AMD GPUs), run:
PYTORCH_ENABLE_MPS_FALLBACK=1 python web_demo_2.5.py --device mps
```
## Online Demo
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).
## Install ## Install
@@ -582,24 +602,6 @@ PYTORCH_ENABLE_MPS_FALLBACK=1 python test.py
### Deployment on Mobile Phone ### Deployment on Mobile Phone
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. 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.
### WebUI Demo
<details>
<summary>Click to see how to deploy WebUI demo on different devices </summary>
```shell
pip install -r requirements.txt
```
```shell
# For NVIDIA GPUs, run:
python web_demo_2.5.py --device cuda
# For Mac with MPS (Apple silicon or AMD GPUs), run:
PYTORCH_ENABLE_MPS_FALLBACK=1 python web_demo_2.5.py --device mps
```
</details>
### Inference with llama.cpp<a id="inference-with-llamacpp"></a> ### Inference with llama.cpp<a id="inference-with-llamacpp"></a>
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). 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).