Instructions to use jdopensource/JoyAI-Image-Edit-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdopensource/JoyAI-Image-Edit-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jdopensource/JoyAI-Image-Edit-Diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "JoyImageEditTransformer3DModel", | |
| "_diffusers_version": "0.38.0.dev0", | |
| "attn_backend": "torch_spda", | |
| "dit_modulation_type": "wanx", | |
| "enable_activation_checkpointing": false, | |
| "heads_num": 32, | |
| "hidden_size": 4096, | |
| "in_channels": 16, | |
| "is_repa": false, | |
| "mlp_width_ratio": 4.0, | |
| "mm_double_blocks_depth": 40, | |
| "out_channels": 16, | |
| "patch_size": [ | |
| 1, | |
| 2, | |
| 2 | |
| ], | |
| "repa_layer": 13, | |
| "rope_dim_list": [ | |
| 16, | |
| 56, | |
| 56 | |
| ], | |
| "rope_theta": 10000, | |
| "rope_type": "rope", | |
| "text_states_dim": 4096, | |
| "unpatchify_new": true | |
| } | |