Instructions to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF", filename="Qwen2.5-VL-7B-Instruct-abliterated/Qwen2.5-VL-7B-Instruct-abliterated.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "\"Astronaut riding a horse\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Phil2Sat/Qwen-Image-Edit-Rapid-AIO-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 Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Phil2Sat/Qwen-Image-Edit-Rapid-AIO-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 Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Phil2Sat/Qwen-Image-Edit-Rapid-AIO-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 Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
Use Docker
docker model run hf.co/Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with Ollama:
ollama run hf.co/Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
- Unsloth Studio new
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-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 Phil2Sat/Qwen-Image-Edit-Rapid-AIO-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 Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF to start chatting
- Pi new
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with Docker Model Runner:
docker model run hf.co/Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
- Lemonade
How to use Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Phil2Sat/Qwen-Image-Edit-Rapid-AIO-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen-Image-Edit-Rapid-AIO-GGUF-Q4_K_M
List all available models
lemonade list
Abliterated TE?
Hey, thanks for the gguf
My question is what exactly does the abliterated TE bring to the table?
Do you have some example comparisons?
So far I'm seeing the same results, just that i get slight pixel shift and color shift when using the Abliterated vs normal.