Instructions to use jpuri/LGM-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jpuri/LGM-full with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jpuri/LGM-full", 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
| license: mit | |
| pipeline_tag: image-to-3d | |
| # LGM Full | |
| This custom pipeline encapsulates the full [LGM](https://huggingface.co/ashawkey/LGM) pipeline, including [multi-view diffusion](https://huggingface.co/ashawkey/imagedream-ipmv-diffusers). | |
| It is provided as a resource for the [ML for 3D Course](https://huggingface.co/learn/ml-for-3d-course). | |
| Original LGM paper: [LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation](https://huggingface.co/papers/2402.05054). | |