Instructions to use openbmb/MiniCPM-V-2_6-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openbmb/MiniCPM-V-2_6-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="openbmb/MiniCPM-V-2_6-gguf",
	filename="ggml-model-IQ3_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use openbmb/MiniCPM-V-2_6-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf openbmb/MiniCPM-V-2_6-gguf:Q4_K_M

Use Docker

docker model run hf.co/openbmb/MiniCPM-V-2_6-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use openbmb/MiniCPM-V-2_6-gguf with Ollama:
```
ollama run hf.co/openbmb/MiniCPM-V-2_6-gguf:Q4_K_M
```

Unsloth Studio new

How to use openbmb/MiniCPM-V-2_6-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for openbmb/MiniCPM-V-2_6-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for openbmb/MiniCPM-V-2_6-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for openbmb/MiniCPM-V-2_6-gguf to start chatting

Docker Model Runner
How to use openbmb/MiniCPM-V-2_6-gguf with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM-V-2_6-gguf:Q4_K_M
```

Lemonade

How to use openbmb/MiniCPM-V-2_6-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull openbmb/MiniCPM-V-2_6-gguf:Q4_K_M

Run and chat with the model

lemonade run user.MiniCPM-V-2_6-gguf-Q4_K_M

List all available models

lemonade list

MiniCPM-V 2.6

Prepare models and code

Download MiniCPM-V-2_6 PyTorch model from huggingface to "MiniCPM-V-2_6" folder.

Clone llama.cpp:

git clone git@github.com:OpenBMB/llama.cpp.git
cd llama.cpp
git checkout minicpmv-main

Usage of MiniCPM-V 2.6

Convert PyTorch model to gguf files (You can also download the converted gguf by us)

python ./examples/llava/minicpmv-surgery.py -m ../MiniCPM-V-2_6
python ./examples/llava/minicpmv-convert-image-encoder-to-gguf.py -m ../MiniCPM-V-2_6 --minicpmv-projector ../MiniCPM-V-2_6/minicpmv.projector --output-dir ../MiniCPM-V-2_6/ --image-mean 0.5 0.5 0.5 --image-std 0.5 0.5 0.5 --minicpmv_version 3
python ./convert_hf_to_gguf.py ../MiniCPM-V-2_6/model

# quantize int4 version
./llama-quantize ../MiniCPM-V-2_6/model/ggml-model-f16.gguf ../MiniCPM-V-2_6/model/ggml-model-Q4_K_M.gguf Q4_K_M

Build for Linux or Mac

make
make llama-minicpmv-cli

Inference on Linux or Mac

# run f16 version
./llama-minicpmv-cli -m ../MiniCPM-V-2_6/model/ggml-model-f16.gguf --mmproj ../MiniCPM-V-2_6/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -p "What is in the image?"

# run quantized int4 version
./llama-minicpmv-cli -m ../MiniCPM-V-2_6/model/ggml-model-Q4_K_M.gguf --mmproj ../MiniCPM-V-2_6/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg  -p "What is in the image?"

# or run in interactive mode
./llama-minicpmv-cli -m ../MiniCPM-V-2_6/model/ggml-model-Q4_K_M.gguf --mmproj ../MiniCPM-V-2_6/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -i