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
| { | |
| "per_channel": true, | |
| "reduce_range": true, | |
| "per_model_config": { | |
| "model": { | |
| "op_types": [ | |
| "Unsqueeze", | |
| "Shape", | |
| "Transpose", | |
| "Sqrt", | |
| "Gather", | |
| "Slice", | |
| "Erf", | |
| "Div", | |
| "Reshape", | |
| "Add", | |
| "Cast", | |
| "Sub", | |
| "Concat", | |
| "ReduceMean", | |
| "Mul", | |
| "Conv", | |
| "Constant", | |
| "Resize", | |
| "Softmax", | |
| "Pow", | |
| "Relu", | |
| "MatMul" | |
| ], | |
| "weight_type": "QUInt8" | |
| } | |
| } | |
| } |