Instructions to use suvadityamuk/TripoSG-diffusers-3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use suvadityamuk/TripoSG-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/TripoSG-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 vae/config.json from suvadityamuk/TripoSG-diffusers-3d: direct link, hf CLI and curl.
- Browser
- Download file 259 Bytes
-
https://huggingface.co/suvadityamuk/TripoSG-diffusers-3d/resolve/main/vae/config.json
- Command line
-
hf download hf://suvadityamuk/TripoSG-diffusers-3d/vae/config.json
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curl -L -o config.json https://huggingface.co/suvadityamuk/TripoSG-diffusers-3d/resolve/main/vae/config.json
259 Bytes
| { | |
| "_class_name": "TripoSGVAEDecoder", | |
| "_diffusers_version": "0.41.0.dev0", | |
| "embed_frequency": 8, | |
| "embed_include_pi": false, | |
| "in_channels": 3, | |
| "latent_channels": 64, | |
| "num_attention_heads": 8, | |
| "num_layers_decoder": 16, | |
| "width_decoder": 1024 | |
| } | |