Instructions to use chibifire/omnigen2-editscore-desktop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chibifire/omnigen2-editscore-desktop 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("chibifire/omnigen2-editscore-desktop", 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
omnigen2-editscore-desktop
Desktop packages of OmniGen2 with the EditScore7B-v1.1 LoRA. The program edits an image from an instruction, on your GPU. The page with the instructions is the Space chibifire/omnigen2-editscore.
Files
omnigen2-editscore-macos-arm64.zip: macOS, Apple silicon (Metal).omnigen2-editscore-windows-x86_64.zip: Windows, NVIDIA GPU (CUDA 12).omnigen2-editscore-linux-x86_64.tar: Linux, NVIDIA GPU (CUDA 12).SHA256SUMS: the checksums of the three files.
Each package contains a packed Python environment (pixi-pack), the OmniGen2 inference code, a start script and the weights in the folder w: chibifire/omnigen2-base-df5dca8a with the OmniGen2/OmniGen2-EditScore7B-v1.1 LoRA merged in, stored in 4 bits (4.6 GB). On NVIDIA, the program expands the weights to BF16 when it starts. The program does not connect to other computers. The edit page loads only from this computer.
Source
The package script and the program are in the desktop/ folder of V-Sekai-fire/interactor-omnigen2, a fork of VectorSpaceLab/OmniGen2.
Licence
Apache License 2.0, as OmniGen2 and the EditScore7B-v1.1 LoRA. The packed environment holds open source packages from conda-forge with their own licences.
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Model tree for chibifire/omnigen2-editscore-desktop
Base model
OmniGen2/OmniGen2