POCKET-MODELs
Collection
9 items β’ Updated β’ 16
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", torch_dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]POCKET-Image is VIDRAFT's on-device text-in-image system. It places character-perfect text in any language β Korean Β· δΈζ Β· ζ₯ζ¬θͺ Β· Ψ§ΩΨΉΨ±Ψ¨ΩΨ© Β· ΰΉΰΈΰΈ’ Β· Latin and more β onto any scene you describe. Built on the open, commercial-friendly Z-Image foundation and VIDRAFT's POCKET-Core engine.
Where global models smear non-Latin scripts ("μλ νμΈμ" β "μγ κΈ°"), POCKET-Image renders every glyph exactly.
| Machine | Peak memory |
|---|---|
| RTX 3050 / 4060 | 8.6 GB |
| RTX 2060 (6 GB, offloaded) | 4.5 GB |
| MacBook (M1 ProβM4, 16 GB+) | 13.4 GB |
Base model: Tongyi-MAI/Z-Image (Apache-2.0). Engine: VIDRAFT POCKET-Core.
Big models, small hardware. No GPU, no cloud.
Models
Demos & tools (Spaces)
Base model
Tongyi-MAI/Z-Image