Instructions to use xixircc/MetaRigCapture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xixircc/MetaRigCapture with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xixircc/MetaRigCapture", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 326a40ac1db959b89a8800aff07b1c10b8f2db9b5389d56521f92dd3ce7fe101
- Size of remote file:
- 4.93 GB
- SHA256:
- 0ff582dff6e19b08278378cfc244cf7203c6f70e3dcaba492ec39f9abb9be3d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.