Instructions to use unsloth/Z-Image-Turbo-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use unsloth/Z-Image-Turbo-FP8 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-FP8", dtype=torch.bfloat16, device_map="cuda") prompt = "cute sloth typing on a computer (INT8)" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Unsloth Desktop
Commit History
24 days ago
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Add safetensors
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Add ConvRot
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Add files using upload-large-folder tool
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Fix model card tags
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Upload README.md with huggingface_hub
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Upload Z-Image-Turbo-text_encoder-FP8.pt with huggingface_hub
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Set base_model and add unsloth tag
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Add quantization header and logos
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Add sample widget and showcase table
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Rename checkpoints to model-name files
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Add official model card and quantized samples
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initial commit
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