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
- Draw Things
- DiffusionBee
- Unsloth Studio new
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, )

- Xet hash:
- 7a932f3b3cabb5d0c07f527b8fe5f2b6780fe9ea5a3442aef48a70c60e9fa901
- Size of remote file:
- 7.7 MB
- SHA256:
- 96c16b2c8d8dc67bb92ecc22d54b9955ab55136977f515bb76f4b2eb42eb3cdb
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