Instructions to use p4ss3r2/wan22_Pupil_Transition_LoRa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use p4ss3r2/wan22_Pupil_Transition_LoRa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-I2V-A14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("p4ss3r2/wan22_Pupil_Transition_LoRa") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
training hyperparameters and scripts
#1
by theKinsley - opened
Thanks for sharing the LoRA weight. The results are really impressive!
I was wondering if it would be possible to share some details about the training hyperparameters you used. If it's convenient, it would be even more helpful to have the full training script (starting with accelerate launch ...) so that I can better understand and reproduce your setup.
Thank you again for your amazing work!