Instructions to use smartdigitalnetworks/beyond-reality-z-image-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use smartdigitalnetworks/beyond-reality-z-image-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("smartdigitalnetworks/beyond-reality-z-image-diffusers", 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
- Draw Things
- DiffusionBee
| license: apache-2.0 | |
| base_model: Tongyi-MAI/Z-Image-Turbo | |
| tags: | |
| - diffusers | |
| - text-to-image | |
| - z-image | |
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| # beyond-reality-z-image-diffusers | |
| This is a converted version of the Beyond Reality Z-Image transformer, converted to diffusers format for use with the `ZImagePipeline`. | |
| ## Model Description | |
| This transformer is based on [Beyond Reality Z-Image](https://huggingface.co/Nurburgring/BEYOND_REALITY_Z_IMAGE), converted from ComfyUI format to diffusers format. | |
| ## Usage | |
| ```python | |
| import torch | |
| from diffusers import ZImagePipeline, ZImageTransformer2DModel | |
| # Load the custom transformer | |
| transformer = ZImageTransformer2DModel.from_pretrained( | |
| "linoyts/beyond-reality-z-image-diffusers", | |
| torch_dtype=torch.bfloat16 | |
| ) | |
| # Load the pipeline with custom transformer | |
| pipe = ZImagePipeline.from_pretrained( | |
| "Tongyi-MAI/Z-Image-Turbo", | |
| transformer=transformer, | |
| torch_dtype=torch.bfloat16, | |
| ) | |
| pipe.to("cuda") | |
| # Generate an image | |
| prompt = "A beautiful landscape with mountains and a lake, photorealistic, 8k" | |
| image = pipe( | |
| prompt=prompt, | |
| num_inference_steps=8, | |
| guidance_scale=0.0, # Z-Image-Turbo uses guidance_scale=0 | |
| width=1024, | |
| height=1024, | |
| ).images[0] | |
| image.save("output.png") | |
| ``` | |
| ## Original Model | |
| - **Source**: [Nurburgring/BEYOND_REALITY_Z_IMAGE](https://huggingface.co/Nurburgring/BEYOND_REALITY_Z_IMAGE) | |
| - **Base Architecture**: [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo) | |
| ## Conversion Details | |
| The model was converted from ComfyUI format to diffusers format with the following key transformations: | |
| - Removed `model.diffusion_model.` prefix from all keys | |
| - Renamed `x_embedder` to `all_x_embedder.2-1` | |
| - Renamed `final_layer` to `all_final_layer.2-1` | |
| - Split `attention.qkv` into `attention.to_q`, `attention.to_k`, `attention.to_v` | |
| - Renamed `attention.out` to `attention.to_out.0` | |
| - Renamed `attention.q_norm` to `attention.norm_q` | |
| - Renamed `attention.k_norm` to `attention.norm_k` | |