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:
- 4a442901ca136f1de861efe69d24e62d36f4dc2c8ce5bd28d2f7e4322a4d398a
- Size of remote file:
- 3.44 GB
- SHA256:
- 70bd61af38282924eec16a3383b9592c977997c8a01154d64c7d792ffd1fb8ee
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