Instructions to use xpanceo-team/mattergen-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xpanceo-team/mattergen-base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xpanceo-team/mattergen-base", 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
| { | |
| "_class_name": "MatterGenPipeline", | |
| "_diffusers_version": "0.33.1", | |
| "atomic_numbers_scheduler": [ | |
| "crystal_diffusers", | |
| "D3PMScheduler" | |
| ], | |
| "cell_scheduler": [ | |
| "crystal_diffusers", | |
| "VariancePreservingScheduler" | |
| ], | |
| "condition_encoder": [ | |
| "crystal_diffusers", | |
| "ConditionEncoder" | |
| ], | |
| "frac_coords_scheduler": [ | |
| "crystal_diffusers", | |
| "VarianceExplodingScheduler" | |
| ], | |
| "gnn": [ | |
| "crystal_diffusers", | |
| "GemNetTWrapper" | |
| ], | |
| "score_model": [ | |
| "crystal_diffusers", | |
| "MatterGenModel" | |
| ] | |
| } | |