Text-to-Image
Diffusers
Safetensors
English
ZImagePipeline
unsloth
4bit
quantized
bitsandbytes
8-bit precision
Instructions to use unsloth/Z-Image-Turbo-unsloth-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use unsloth/Z-Image-Turbo-unsloth-bnb-4bit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("unsloth/Z-Image-Turbo-unsloth-bnb-4bit", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Unsloth Studio
How to use unsloth/Z-Image-Turbo-unsloth-bnb-4bit 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/Z-Image-Turbo-unsloth-bnb-4bit 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/Z-Image-Turbo-unsloth-bnb-4bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/Z-Image-Turbo-unsloth-bnb-4bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unsloth/Z-Image-Turbo-unsloth-bnb-4bit", max_seq_length=2048, )
Upload .gitattributes with huggingface_hub
Browse files- .gitattributes +11 -0
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