| library_name: diffusers | |
| tags: | |
| - z-image | |
| - z-image-edit | |
| - image-editing | |
| - diffusers | |
| - safetensors | |
| base_model: | |
| - John2386/fullgreed | |
| - Anjoe/z-image-edit | |
| # Fullgreed Edit | |
| Fullgreed Edit is a Z-Image-Edit-style Diffusers repository. The transformer weights were created by transferring the Fullgreed delta onto the Z-Image-Edit donor transformer architecture: | |
| `Z-Image-Edit + (John2386/fullgreed - Z-Image base)` | |
| ## What is included | |
| - Fullgreed edit transformer: `transformer/diffusion_pytorch_model.safetensors` | |
| - Z-Image-Edit transformer config with `in_channels: 32` | |
| - Qwen3-4B text encoder files from the edit donor | |
| - tokenizer files from the edit donor | |
| - Flux/Z-Image VAE files from the edit donor | |
| - FlowMatch scheduler config from the edit donor | |
| - Diffusers `model_index.json` | |
| ## Important note | |
| This is not a paper-scale retraining of Z-Image-Edit. It is a Fullgreed delta transplant into the Z-Image-Edit donor architecture, with the missing non-transformer runtime components mirrored from the donor repo. | |
| A true paper-style model would require continued edit training on paired source/instruction/target images. This repo is intended to preserve the donor edit structure while carrying the Fullgreed visual style. | |
| ## Smoke testing | |
| Use a Z-Image-Edit-compatible runner. The current public Diffusers `ZImagePipeline` support may lag behind the paper-style source-image editing API, so if a loader exposes only text-to-image generation, use the donor/edit runner that supports reference-image latents. | |