Text-to-3D
Diffusers
Safetensors
English
StableDiffusionLDM3DPipeline
stable-diffusion
stable-diffusion-diffusers
text-to-image
Eval Results (legacy)
Instructions to use Intel/ldm3d-4c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/ldm3d-4c 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-4c", 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
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README.md
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@@ -30,7 +30,7 @@ This research paper proposes a Latent Diffusion Model for 3D (LDM3D) that genera
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You can use this model to generate RGB and depth map given a text prompt.
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A short video summarizing the approach can be found at [this url](https://t.ly/tdi2) and a VR demo can be found [here](https://www.youtube.com/watch?v=3hbUo-hwAs0).
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### How to use
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You can use this model to generate RGB and depth map given a text prompt.
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A short video summarizing the approach can be found at [this url](https://t.ly/tdi2) and a VR demo can be found [here](https://www.youtube.com/watch?v=3hbUo-hwAs0).
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A demo is also accessible on [Spaces](https://huggingface.co/spaces/Intel/ldm3d)
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### How to use
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