Instructions to use 2hzXie/LGM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 2hzXie/LGM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("2hzXie/LGM", 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
metadata
license: mit
pipeline_tag: image-to-3d
LGM Full
This custom pipeline encapsulates the full LGM pipeline, including multi-view diffusion.
It is provided as a resource for the ML for 3D Course.
Original LGM paper: LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation.