Instructions to use moks1k/alisaa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use moks1k/alisaa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ostris/wan22_i2v_14b_orbit_shot_lora", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("moks1k/alisaa") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 39fad4511bf1b92a68479fcfc5d64d81f6fe63e292fbca582dfdd00721e28cb0
- Size of remote file:
- 307 MB
- SHA256:
- c447237090f19449ba2cb087f106ccb0ee068320c3a88fdc98c3ef8400595fae
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