Instructions to use vs211/comfy-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vs211/comfy-models 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("vs211/comfy-models") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 177cb68ca7eedb2148af755b4b2f33cc41ab51281056e96476cd29c52991b130
- Size of remote file:
- 14.5 GB
- SHA256:
- 8a51de3ec770a238d5641c261c324cb670dbdd895e05bdafbce654edc62c880f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.