Instructions to use wolfer45/jumpscare-low with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/jumpscare-low 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("wolfer45/jumpscare-low") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 40a74253d20f67a59219ef3052bb4d2eca8ae598ad3fa969cb313cdd50638500
- Size of remote file:
- 38.4 MB
- SHA256:
- 7878bf2eb45e74395e5b9f4bb201d3e50a9aa8b60e668081311c788c6dfd6eb5
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