Diffusers
GMDiTPipeline
Lakonik nielsr HF Staff commited on
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1 Parent(s): c8bcefd

Add pipeline tag and library name to model card (#1)

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- Add pipeline tag and library name to model card (1a9912b80598a7c91ab2d9a069603524a97c86c6)


Co-authored-by: Niels Rogge <[email protected]>

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  1. README.md +4 -2
README.md CHANGED
@@ -1,5 +1,7 @@
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  ---
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  license: apache-2.0
 
 
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  ---
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  # Gaussian Mixture Flow Matching Models (GMFlow)
@@ -27,7 +29,7 @@ Model used in the paper:
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  ## Usage
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- Please first install the [official code repository](https://github.com/Lakonik/GMFlow).
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  We provide a Diffusers pipeline for easy inference. The following code demonstrates how to sample images from the pretrained GM-DiT model using the GM-ODE 2 solver and the GM-SDE 2 solver.
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@@ -86,4 +88,4 @@ for i, (word, image) in enumerate(zip(words, output.images)):
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  primaryClass={cs.LG},
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  url={https://arxiv.org/abs/2504.05304},
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  }
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- ```
 
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  ---
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  license: apache-2.0
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+ pipeline_tag: unconditional-image-generation
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+ library_name: diffusers
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  ---
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  # Gaussian Mixture Flow Matching Models (GMFlow)
 
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  ## Usage
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+ Please first install the [official code repository](https://github.com/Lakonik/GMFlow).\
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  We provide a Diffusers pipeline for easy inference. The following code demonstrates how to sample images from the pretrained GM-DiT model using the GM-ODE 2 solver and the GM-SDE 2 solver.
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  primaryClass={cs.LG},
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  url={https://arxiv.org/abs/2504.05304},
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  }
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+ ```