Instructions to use VAST-AI/MIDI-3D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VAST-AI/MIDI-3D with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("VAST-AI/MIDI-3D", 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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license: apache-2.0
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license: apache-2.0
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pipeline_tag: image-to-3d
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# MIDI-3D
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<!-- Provide a quick summary of what the model is/does. -->
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MIDI is a 3D generative model for single image to compositional 3D scene generation. It was introduced in the paper [MIDI: Multi-Instance Diffusion for Single Image to 3D Scene Generation](https://huggingface.co/papers/2412.03558).
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Project page: https://huanngzh.github.io/MIDI-Page/
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Code: https://github.com/VAST-AI-Research/MIDI-3D
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