Instructions to use slzd/Z-Image-Base-0.36.0.dev0-fp32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use slzd/Z-Image-Base-0.36.0.dev0-fp32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("slzd/Z-Image-Base-0.36.0.dev0-fp32", 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
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Download README.md from slzd/Z-Image-Base-0.36.0.dev0-fp32: direct link, hf CLI and curl.
- Browser
- Download file 581 Bytes
-
https://huggingface.co/slzd/Z-Image-Base-0.36.0.dev0-fp32/resolve/main/README.md
- Command line
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hf download hf://slzd/Z-Image-Base-0.36.0.dev0-fp32/README.md
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curl -L -o README.md https://huggingface.co/slzd/Z-Image-Base-0.36.0.dev0-fp32/resolve/main/README.md
581 Bytes
metadata
license: apache-2.0
Z-Image Base v0.36.0.dev0 (FP32)
This repository provides a high-fidelity FP32 (Full Precision) mirror of the Z-Image base model.
- Source Commit: 1ac663b (Tongyi-MAI/Z-Image)
- Precision: Float32 (Full Precision)
Usage in Ostris AI Toolkit
To use this model for your training runs, replace the default model path in your configuration by:
Model Name/Path:
slzd/Z-Image-Base-0.36.0.dev0-fp32
Instead of:
Tongyi-MAI/Z-Image