Instructions to use diffusers-modular/krea2-edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-modular/krea2-edit 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("diffusers-modular/krea2-edit", 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
File size: 602 Bytes
4684d79 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | """Entry point for the Krea 2 reference-image edit modular blocks (loaded via `trust_remote_code`).
Importing this module also registers `Krea2Transformer2DModel` into the `diffusers` namespace so that
`ModularPipeline` component loading can resolve the transformer referenced as
`["diffusers", "Krea2Transformer2DModel"]` in the base `krea/Krea-2-Turbo` `model_index.json`.
"""
from .transformer_krea2 import Krea2Transformer2DModel # noqa: F401 (registers into diffusers namespace)
from .modular_blocks_krea2_edit import Krea2EditBlocks
__all__ = ["Krea2EditBlocks", "Krea2Transformer2DModel"]
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