Instructions to use DhruvDecoder/model_3d_diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DhruvDecoder/model_3d_diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DhruvDecoder/model_3d_diffuser", 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
Commit History
-
minify, update requirements
dylanebertbf7666a -
minify
dylanebert6b83d25 -
isort
dylaneberta283418 -
embed mv_unet
dylaneberta3fbb44 -
rename pipeline
dylanebert1144e46 -
initial commit
dylanebert9a06fc4
-
Update requirements.txt
Unverified signature8b318ef
-
add elevation in call
e94af11
-
remove grad checkpointing
48e8b1b
-
finalize remote weights
e6a1dec -
merged to one file for loading from huggingface...
0cf459d -
clean up...
1d16c41 -
finally, everything works locally
53fc90d -
both worked... but imagedream quality is unmatched
3a2ea0a -
draft imagedream, before merge
af95a32 -
imagedream framework
8241d5f -
rename
5d590ff -
fix mvdream
b861db3
-
further clean!
f0e1e27 -
reformat, further clean
8747d5d -
clean up
fbd4c7f -
ign
2bc848f -
init
a8a63dd