minicpm-v4_5_ollama.md

MiniCPM-V 4.5 - Ollama

1. Install Ollama

• macOS: Download from https://ollama.com/download/Ollama.dmg.

• Windows: Download from https://ollama.com/download/OllamaSetup.exe.

• Linux: curl -fsSL https://ollama.com/install.sh | sh, or refer to the guide from ollama.

• Docker: The official Ollama Docker image ollama/ollama is available on Docker Hub.

Build Ollama locally

Environment requirements:

• go version 1.22 or above
• cmake version 3.24 or above
• C/C++ Compiler e.g. Clang on macOS, TDM-GCC (Windows amd64) or llvm-mingw (Windows arm64), GCC/Clang on Linux.

Clone OpenBMB Ollama Fork:

git clone https://github.com/tc-mb/ollama.git
cd ollama
git checkout MIniCPM-V

Then build and run Ollama from the root directory of the repository:

go build .
./ollama serve

2. Quick Start

The MiniCPM-V 4.5 model can be used directly:

./ollama run openbmb/minicpm-v4.5

Command Line

Separate the input prompt and the image path with space.

What is in the picture? xx.jpg

API

with open(image_path, 'rb') as image_file:
    # Convert the image file to a base64 encoded string
    encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
    data = {
    "model": "minicpm-v4.5",
    "prompt": query,
    "stream": False,
    "images": [encoded_string] # The 'images' list can hold multiple base64-encoded images.
    }

    # Set request URL
    url = "http://localhost:11434/api/generate"
    response = requests.post(url, json=data)

    return response

3. Customize model

If the method above fails, please refer to the following guide.

Download GGUF Model

• HuggingFace: https://huggingface.co/openbmb/MiniCPM-V-4_5-gguf
• ModelScope: https://modelscope.cn/models/OpenBMB/MiniCPM-V-4_5-gguf

Create a ModelFile

Create and edit a ModelFile:

vim minicpmv4.5.Modelfile

The content of the Modelfile should be as follows:

FROM ./MiniCPM-V-4_5/model/ggml-model-Q4_K_M.gguf
FROM ./MiniCPM-V-4_5/mmproj-model-f16.gguf

TEMPLATE """{{- if .Messages }}{{- range $i, $_ := .Messages }}{{- $last := eq (len (slice $.Messages $i)) 1 -}}<|im_start|>{{ .Role }}{{ .Content }}{{- if $last }}{{- if (ne .Role "assistant") }}<|im_end|><|im_start|>assistant{{ end }}{{- else }}<|im_end|>{{ end }}{{- end }}{{- else }}{{- if .System }}<|im_start|>system{{ .System }}<|im_end|>{{ end }}{{ if .Prompt }}<|im_start|>user{{ .Prompt }}<|im_end|>{{ end }}<|im_start|>assistant{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}"""

SYSTEM """You are a helpful assistant."""

PARAMETER top_p 0.8
PARAMETER num_ctx 4096
PARAMETER stop ["<|im_start|>","<|im_end|>"]
PARAMETER temperature 0.7

Parameter Descriptions:

first from	second from	num_ctx
Your language GGUF model path	Your vision GGUF model path	Max Model length

Create Ollama Model

./ollama create minicpm-v4.5 -f minicpmv4.5.Modelfile

Run

In a new terminal window, run the model instance:

./ollama run minicpm-v4.5

Input Prompt

Enter the prompt and the image path, separated by a space.

What is in the picture? xx.jpg