README.md

---
language:
- zh
- en
base_model:
- openbmb/MiniCPM-V-4
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- MiniCPM
- MiniCPM-V-4
---

# MiniCPM-V-4

## Convert tools links:

For those who are interested in model conversion, you can try to export axmodel through the original repo : 
https://huggingface.co/openbmb/MiniCPM-V-4

[How to Convert LLM from Huggingface to axmodel](https://github.com/Jordan-5i/MiniCPM-o/blob/main/ax_convert/readme.md) 

## Support Platform

- AX650
  - AX650N DEMO Board
  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
  - [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)


## How to use

Download all files from this repository to the device

```
root@ax650:~/wangjian/minicpm-v-4# tree -L 1
.
├── embed_tokens.pth
├── minicpm-v-4_axmodel
├── minicpmv4_tokenizer
├── resampler.axmodel
├── run_axmodel.py
├── show_demo.jpg
└── siglip.axmodel
```
install transformers

```
pip install transformers==4.51.0
```

## Inference with AX650 Host on AX650 DEMO Board

run following cmd：

```bash
python3 run_axmodel.py -i show_demo.jpg -q "What is the landform in the picture?"
```
input image：
![demo.jpg](./show_demo.jpg)

minicpm-v-4 output:

```bash
question1 = "What is the landform in the picture?"

answer1 = The landform in the picture is a karst topography, characterized by its unique and dramatic appearance with steep limestone cliffs rising from the water' s surface. This type of landscape is commonly found in regions with significant geological activity, such as China's Li River.
```