Instructions to use Thekingbalxd/z-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Thekingbalxd/z-image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Thekingbalxd/z-image", 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
| { | |
| "add_skip_keys": false, | |
| "dequantize_fp32": false, | |
| "group_size": 0, | |
| "is_integer": true, | |
| "is_training": false, | |
| "modules_dtype_dict": {}, | |
| "modules_to_not_convert": [ | |
| "all_x_embedder", | |
| "cap_embedder", | |
| "all_final_layer", | |
| "t_embedder", | |
| "layers.0.adaLN_modulation.0.weight" | |
| ], | |
| "non_blocking": false, | |
| "quant_conv": false, | |
| "quant_method": "sdnq", | |
| "quantization_device": null, | |
| "quantized_matmul_dtype": null, | |
| "return_device": null, | |
| "svd_rank": 32, | |
| "svd_steps": 8, | |
| "use_grad_ckpt": true, | |
| "use_quantized_matmul": false, | |
| "use_quantized_matmul_conv": false, | |
| "use_static_quantization": true, | |
| "use_stochastic_rounding": false, | |
| "use_svd": true, | |
| "weights_dtype": "uint4" | |
| } | |