Instructions to use unsloth/Qwen-Image-Layered-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use unsloth/Qwen-Image-Layered-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 unsloth/Qwen-Image-Layered-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 unsloth/Qwen-Image-Layered-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/Qwen-Image-Layered-GGUF to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unsloth/Qwen-Image-Layered-GGUF", max_seq_length=2048, )
Diffusers run gguf?
#2
by gabbo1995 - opened
Is there a way to run it with diffusers in python? Could you please provide an adapted example of how to load the DiT in gguf in diffusers? Thank you so much for your contribution!
We're working on a guide, for now you'll need to use something like ComfyUI
Thank you!!
Diffusers need to compile gguf in every running , very bad. Can you make it work like ComfyUI-GGUF without compiling. If diffusers can have gguf with cpp speed, it will be great. For now ,diffusers can not match comfyui with gguf and adaptive vram . Comfyui can run LTX2 with just 1G vram and less than 32G ram.
Is there a way now to run this gguf model with diffusers or llama.cpp?