Instructions to use B4100/pretzel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use B4100/pretzel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TheRaf7/ultra-real-wan2.2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("B4100/pretzel") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4946ef4f30a68950f1ad52745577d8dfa2af8e08b726a4931678998b4072b1ac
- Size of remote file:
- 307 MB
- SHA256:
- ae39bb6e42c377824ff9ecee5b4b908dde63cea8953226eac7b7a435b58f7e0f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.