Instructions to use gucci233/FlexPart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gucci233/FlexPart with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gucci233/FlexPart", 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
Add model card with metadata, paper link, and code link
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by nielsr HF Staff - opened
README.md
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license: apache-2.0
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license: apache-2.0
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library_name: diffusers
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pipeline_tag: image-to-3d
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# FlexPart
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FlexPart is a unified image-to-3D part generation framework that supports variable-granularity geometric conditions, ranging from sparse points to bounding boxes and segmentation masks, within a single model. It generates separate, assemblable 3D parts from a single image.
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This model is presented in the paper [A Unified Framework for Image-to-3D Part Generation via Variable Granularity](https://huggingface.co/papers/2610.31671).
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The code and usage instructions are available in the official GitHub repository: [https://github.com/Gucci233/FlexPart](https://github.com/Gucci233/FlexPart).
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