Instructions to use WILDFAL/odevalka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WILDFAL/odevalka with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nunchaku-tech/nunchaku-qwen-image-edit-2509", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("WILDFAL/odevalka") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
.png)
- Xet hash:
- 7139482d5f3d9973ff8745be7514f74ba24d610308795fefd31491934faedfd9
- Size of remote file:
- 11.2 kB
- SHA256:
- 3ee50dd87956e78e3fc8f4cc30e3d7591db9d3e2233be104191b0bc106ac3a96
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.