Image-Text-to-Text
GGUF
English
Portuguese
mark-vl
mark-ai
multimodal
vision-language
ocr
spatial-reasoning
pixel-shuffle
ollama
Instructions to use miceworks/Mark-VL-2.2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use miceworks/Mark-VL-2.2B with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf miceworks/Mark-VL-2.2B:Q4_K_M # Run inference directly in the terminal: llama cli -hf miceworks/Mark-VL-2.2B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf miceworks/Mark-VL-2.2B:Q4_K_M # Run inference directly in the terminal: llama cli -hf miceworks/Mark-VL-2.2B: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 miceworks/Mark-VL-2.2B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf miceworks/Mark-VL-2.2B: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 miceworks/Mark-VL-2.2B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf miceworks/Mark-VL-2.2B:Q4_K_M
Use Docker
docker model run hf.co/miceworks/Mark-VL-2.2B:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use miceworks/Mark-VL-2.2B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "miceworks/Mark-VL-2.2B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "miceworks/Mark-VL-2.2B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/miceworks/Mark-VL-2.2B:Q4_K_M
- Ollama
How to use miceworks/Mark-VL-2.2B with Ollama:
ollama run hf.co/miceworks/Mark-VL-2.2B:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use miceworks/Mark-VL-2.2B with Docker Model Runner:
docker model run hf.co/miceworks/Mark-VL-2.2B:Q4_K_M
- Lemonade
How to use miceworks/Mark-VL-2.2B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull miceworks/Mark-VL-2.2B:Q4_K_M
Run and chat with the model
lemonade run user.Mark-VL-2.2B-Q4_K_M
List all available models
lemonade list
- Atomic Chat
feat: upload GGUF weights (mark_vl_2_2b_q4_k_m.gguf)
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- mark_vl_2_2b_q4_k_m.gguf +3 -0
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