Quantized GGUF versions of the Z-Image Turbo by Tongyi-Mai. | Model | Download | | Z-Image Turbo GGUF | Download | | Qwen3-4B (Text Encoder) | unsloth/Qwen3-4B-GGUF
Fonte do modelo
Trecho da fonte
Quantized GGUF versions of the Z-Image Turbo by Tongyi-Mai. | Model | Download | | Z-Image Turbo GGUF | Download | | Qwen3-4B (Text Encoder) | unsloth/Qwen3-4B-GGUF
Recursos relacionados
8 conexõesFontes
1 fonteVerificado 29 de jul.
Artefatos de modelo
1 artefatoTrechos de fonte
3 trechos--- base_model: - Tongyi-MAI/Z-Image-Turbo tags: - text-to-image - image-generation - gguf license: apache-2.0 --- Quantized GGUF versions of the [Z-Image Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo) by Tongyi-Mai. ### 📂 Available Models | Model | Download | |--------|--------------| | Z-Image Turbo GGUF | [Download](https://huggingface.co/jayn7/Z-Image-Turbo-GGUF/tree/main) | | Qwen3-4B (Text Encoder) | [unsloth/Qwen3-4B-GGUF](https://huggingface.co/unsloth/Qwen3-4B-GGUF) ### 📷 Example Comparison    ### Model Information Check out the original model card [Z-Image Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo) for detailed information about the model. ### Usage The model can be used with: - [**ComfyUI-GGUF**](https://github.com/city96/ComfyUI-GGUF) by **city96** - [**Diffusers**](https://github.com/huggingface/diffusers) #### Example Usage <details> <summary>Diffusers</summary> ```sh pip install git+https://github.com/huggingface/diffusers ``` ```py from diffusers import ZImagePipeline, ZImageTransformer2DModel, GGUFQuantizationConfig import torch prompt = "Young Chinese woman in red Hanfu, intricate embroidery. Impeccable makeup, red floral forehead pattern. Elaborate high bun, golden phoenix headdress, red flowers, beads. Holds round folding fan with lady, trees, bird. Neon lightning-bolt lamp (⚡️), bright yellow glow, above extended left palm. Soft-lit outdoor night background, silhouetted tiered pagoda (西安大雁塔), blurred colorful distant lights." height = 1024 width = 1024 seed = 42 #hf_path = "https://huggingface.co/jayn7/Z-Image-Turbo-GGUF/blob/main/z_image_turbo-Q3_K_M.gguf" local_path = "path\to\local\model\z_image_turbo-Q3_K_M.gguf" transformer = ZImageTransformer2DModel.from_single_file( local_path, quantization_config=GGUFQuantizationConfig(compute_dtype=torch.bfloat16), dtype=torch.bfloat16, ) pipeline = ZImagePipeline.from_pretrained( "Tongyi-MAI/Z-Image-Turbo", transformer=transformer, dtype=torch.bfloat16, ).to("cuda")...
Source context: 33468 downloads · 380 likes · Pipeline text-to-image · Repo jayn7/Z-Image-Turbo-GGUF
Source context: 35626 downloads · 378 likes · Pipeline text-to-image · Repo jayn7/Z-Image-Turbo-GGUF