Text-to-Image
Diffusers
Safetensors
English
Korean
ZImagePipeline
image-generation
quantized
bitsandbytes
nf4
4-bit precision
on-device
korean
pocket
vidraft
8-bit precision
Instructions to use FINAL-Bench/POCKET-Image-Zimage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FINAL-Bench/POCKET-Image-Zimage with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FINAL-Bench/POCKET-Image-Zimage", 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
Add POCKET-Zimage-CPU badge (front)
Browse files
README.md
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# 🖼️ POCKET-Image-Zimage — 4-bit (NF4) Z-Image for on-device
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> ### 🆕 **[POCKET-Zimage-CPU](https://huggingface.co/FINAL-Bench/POCKET-Zimage-CPU)** — photoreal **images** in **46 s** on a **CPU only**. No GPU, no CUDA, no Python.
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> [](https://huggingface.co/FINAL-Bench/POCKET-Zimage-CPU) [](https://huggingface.co/spaces/FINAL-Bench/POCKET-Zimage-CPU) []() <!-- POCKET-Zimage-CPU-BADGE -->
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# 🖼️ POCKET-Image-Zimage — 4-bit (NF4) Z-Image for on-device
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