Instructions to use suvadityamuk/sam-3d-objects-diffusers-3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use suvadityamuk/sam-3d-objects-diffusers-3d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("suvadityamuk/sam-3d-objects-diffusers-3d", 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
Download sparse_structure_scheduler/scheduler_config.json from suvadityamuk/sam-3d-objects-diffusers-3d: direct link, hf CLI and curl.
- Browser
- Download file 139 Bytes
-
https://huggingface.co/suvadityamuk/sam-3d-objects-diffusers-3d/resolve/main/sparse_structure_scheduler/scheduler_config.json
- Command line
-
hf download hf://suvadityamuk/sam-3d-objects-diffusers-3d/sparse_structure_scheduler/scheduler_config.json
-
curl -L -o scheduler_config.json https://huggingface.co/suvadityamuk/sam-3d-objects-diffusers-3d/resolve/main/sparse_structure_scheduler/scheduler_config.json
139 Bytes
| { | |
| "_class_name": "TrellisFlowEulerScheduler", | |
| "_diffusers_version": "0.41.0.dev0", | |
| "num_train_timesteps": 1000, | |
| "sigma_min": 0.0 | |
| } | |