Instructions to use Akaneqwq/DualDiff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Akaneqwq/DualDiff 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("Akaneqwq/DualDiff", 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
Download model.manifest.json from Akaneqwq/DualDiff: direct link, hf CLI and curl.
- Browser
- Download file 777 Bytes
-
https://huggingface.co/Akaneqwq/DualDiff/resolve/main/model.manifest.json
- Command line
-
hf download hf://Akaneqwq/DualDiff/model.manifest.json
-
curl -L -o model.manifest.json https://huggingface.co/Akaneqwq/DualDiff/resolve/main/model.manifest.json
777 Bytes
| { | |
| "format": "DualDiff inference checkpoint", | |
| "model": "DualDiff", | |
| "optimizer_removed": true, | |
| "file": "model.pkl", | |
| "size_bytes": 3466253977, | |
| "sha256": "485ce47f2c2f18bfb54ea1ffc1908fce12e7ef1d98cc4e0f7e39afe3d01cf248", | |
| "rank_vae": 4, | |
| "vae_lora_target_modules": 43, | |
| "state_dicts": { | |
| "state_dict_unet": { | |
| "entries": 686, | |
| "tensors": 686, | |
| "parameters": 865910724, | |
| "dtypes": [ | |
| "torch.bfloat16" | |
| ] | |
| }, | |
| "state_dict_vae": { | |
| "entries": 90, | |
| "tensors": 90, | |
| "parameters": 1015452, | |
| "dtypes": [ | |
| "torch.bfloat16" | |
| ] | |
| }, | |
| "state_dict_ref_unet": { | |
| "entries": 686, | |
| "tensors": 686, | |
| "parameters": 865910724, | |
| "dtypes": [ | |
| "torch.bfloat16" | |
| ] | |
| } | |
| } | |
| } | |