| --- |
| license: apache-2.0 |
| base_model: |
| - Tongyi-MAI/Z-Image |
| pipeline_tag: text-to-image |
| library_name: diffusers |
| language: |
| - en |
| - ko |
| tags: |
| - text-to-image |
| - image-generation |
| - quantized |
| - bitsandbytes |
| - nf4 |
| - 4-bit |
| - on-device |
| - korean |
| - pocket |
| - vidraft |
| --- |
| |
| # 🖼️ POCKET-Image-Zimage — 4-bit (NF4) Z-Image for on-device |
|
|
| A **4-bit (NF4) quantized build of [Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image)** (Apache-2.0), |
| packaged by VIDRAFT for **low-VRAM, on-device** image generation — part of the POCKET line. |
|
|
| - 📦 **~6 GB on disk** (transformer + text encoder in NF4, VAE in fp16) |
| - ⚡ **Runs from ~8.6 GB VRAM** (≈**4.5 GB** with CPU offload) — vs **23.3 GB** for bf16 |
| - 🎯 ~2.7–5× smaller footprint, quality on par with the bf16 base |
|
|
| ## Usage |
| ```python |
| import torch |
| from diffusers import ZImagePipeline # or ZImageImg2ImgPipeline / ZImageInpaintPipeline |
| |
| pipe = ZImagePipeline.from_pretrained( |
| "FINAL-Bench/POCKET-Image-Zimage", torch_dtype=torch.bfloat16 |
| ).to("cuda") |
| img = pipe("a serene mountain lake at sunrise, photorealistic", num_inference_steps=20).images[0] |
| img.save("out.png") |
| ``` |
| Requires **`bitsandbytes`** (CUDA). Measured reload + generate peak: ~10.9 GB VRAM. |
| For Apple Silicon / CPU, an `optimum-quanto` int8 build (~13.4 GB) is the portable option. |
|
|
| ## 🎨 The full POCKET-Image system |
| This repo hosts the **quantized base model** only. The headline **character-perfect Korean & |
| multilingual text** feature is delivered by the POCKET-Image *pipeline*, not by these weights alone. |
| Try the full system here: |
|
|
| - **🎨 Studio (generate here):** https://huggingface.co/spaces/FINAL-Bench/POCKET-Image-Studio |
|
|
| Base model: [Tongyi-MAI/Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image) (Apache-2.0) · Quantization: bitsandbytes NF4 · By VIDRAFT. |
|
|
| <!-- POCKET-FAMILY --> |
|
|
| --- |
|
|
| ## 🧩 The POCKET Family — On-device AI by VIDRAFT |
|
|
| *Big models, small hardware. No GPU, no cloud.* |
|
|
| **Models** |
| - 📦 [POCKET-35B-GGUF](https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF) — flagship, PC / server, no GPU |
| - 📦 [POCKET-26B-GGUF](https://huggingface.co/FINAL-Bench/POCKET-26B-GGUF) — compact 26B |
| - 🇰🇷 [POCKET-KR-GGUF](https://huggingface.co/FINAL-Bench/POCKET-KR-GGUF) — Korean, Android |
| - 🍎 [POCKET-KR-MLX](https://huggingface.co/FINAL-Bench/POCKET-KR-MLX) — Korean, iPhone / Mac |
| - 🌍 [POCKET-EN-GGUF](https://huggingface.co/FINAL-Bench/POCKET-EN-GGUF) — English, phone / PC |
| - 🖼️ [POCKET-Image-Zimage](https://huggingface.co/FINAL-Bench/POCKET-Image-Zimage) — 4-bit Z-Image (this repo) |
|
|
| **Demos & tools (Spaces)** |
| - 🎨 [POCKET-Image Studio](https://huggingface.co/spaces/FINAL-Bench/POCKET-Image-Studio) — text-in-image, generate in-page |
| - 🖥️ [POCKET-35B-CPU](https://huggingface.co/spaces/FINAL-Bench/POCKET-35B-CPU) — 35B answering on a CPU |
| - 🖥️ [POCKET-26B-CPU](https://huggingface.co/spaces/FINAL-Bench/POCKET-26B-CPU) — 26B on a CPU |
|
|
| 📚 [Full POCKET collection](https://huggingface.co/collections/FINAL-Bench/pocket-models-6a618ee5d23eafb7e185a5c6) |
|
|
| <!-- /POCKET-FAMILY --> |
|
|
