Instructions to use chenguolin/DiffSplat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chenguolin/DiffSplat with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("chenguolin/DiffSplat", 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
update assets
Browse files- teaser_scrolling.mp4 +0 -3
teaser_scrolling.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:1da814d994a2bc7c551302c055954c18b9a54d21f33917c4c4ec831b5b8eb15f
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size 8634177
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