Text-to-3D
Diffusers
Safetensors
English
StableDiffusionLDM3DPipeline
stable-diffusion
stable-diffusion-diffusers
text-to-image
Eval Results (legacy)
Instructions to use Intel/ldm3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/ldm3d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Intel/ldm3d", 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
- Xet hash:
- ee0092e35089a0d58028770c57a6bf93ce468f16fcb09ecfb3ec1cb3d3c6fa03
- Size of remote file:
- 335 MB
- SHA256:
- 3570304c7bfe36429199d8d5170386930fe5406e1a8f282d3df8eec5a288eda7
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