Instructions to use wolfer45/morphlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/morphlow 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("wolfer45/morphlow") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 794e1bd8082dc065151d3bbd85c01a683a40f55e5c54bf7bf680825ee7663ebe
- Size of remote file:
- 307 MB
- SHA256:
- 87d5d93f8214b19d79fb3b7f666446af65761b63b4f594d22655ff3d8466e1fb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.