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", torch_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
Update README.md
Browse files
README.md
CHANGED
|
@@ -55,8 +55,3 @@ predicted velocity). With `ref_seq_len=0` it is numerically identical to plain K
|
|
| 55 |
- `transformer_krea2.py` — the Krea 2 transformer (with the `ref_seq_len` edit path).
|
| 56 |
- `modular_blocks_krea2*.py`, `encoders.py`, `before_denoise.py`, `denoise.py`, `decoders.py`,
|
| 57 |
`inputs.py`, `modular_pipeline.py` — the modular blocks.
|
| 58 |
-
|
| 59 |
-
Part of the [`diffusers-modular`](https://huggingface.co/diffusers-modular) effort to replicate
|
| 60 |
-
popular ComfyUI / community workflows with Modular Diffusers.
|
| 61 |
-
|
| 62 |
-
> Requires access to the gated `krea/Krea-2-Turbo` weights.
|
|
|
|
| 55 |
- `transformer_krea2.py` — the Krea 2 transformer (with the `ref_seq_len` edit path).
|
| 56 |
- `modular_blocks_krea2*.py`, `encoders.py`, `before_denoise.py`, `denoise.py`, `decoders.py`,
|
| 57 |
`inputs.py`, `modular_pipeline.py` — the modular blocks.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|