Text-to-Image
Diffusers
image-generation
korean
multilingual
hangul
korean-text-rendering
typography
poster
on-device
pocket
vidraft
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", torch_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
metadata
license: apache-2.0
base_model:
- Tongyi-MAI/Z-Image
pipeline_tag: text-to-image
library_name: diffusers
language:
- ko
- en
- zh
- ja
- ar
- th
tags:
- text-to-image
- image-generation
- korean
- multilingual
- hangul
- korean-text-rendering
- typography
- poster
- on-device
- pocket
- vidraft
πΌοΈ POCKET-Image-Zimage β Character-Perfect Text in Any Image
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.
β¨ Highlights
- β 100% accurate text, any language β RTL (Arabic) and complex shaping (Thai, Indic) handled
- πΌοΈ Any background from a prompt β text is optional (empty β pure image)
- β‘ No GPU, no NPU β runs on plain CPU + RAM
- πͺΆ From 4.5 GB footprint Β· π» Windows Β· macOS Β· Linux (RTX or Apple Silicon)
- π Fully local β no cloud, no account
π¨ Try it
- Studio (generate here): https://huggingface.co/spaces/FINAL-Bench/POCKET-Image-Studio
π» On-device footprint (measured)
| 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.
π§© The POCKET Family β On-device AI by VIDRAFT
Big models, small hardware. No GPU, no cloud.
Models
- π¦ POCKET-35B-GGUF β flagship, PC / server, no GPU
- π¦ POCKET-26B-GGUF β compact 26B
- π°π· POCKET-KR-GGUF β Korean, Android
- π POCKET-KR-MLX β Korean, iPhone / Mac
- π POCKET-EN-GGUF β English, phone / PC
- πΌοΈ POCKET-Image-Zimage β character-perfect text in any image
Demos & tools (Spaces)
- π¨ POCKET-Image Studio β text-in-image, generate in-page
- π₯οΈ POCKET-35B-CPU β 35B answering on a CPU
- π₯οΈ POCKET-26B-CPU β 26B on a CPU