huggingface / huggingface/diffusers
implementation of One-step Diffusion with Distribution Matching Distillation
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contributions-welcome
stale
training
- Dominant language
- Python
- Stars
- 34.5k
- Forks
- 7.3k
- Avg merge
- 3d 3h
- Merged PRs (30d)
- 91
Description
Model/Pipeline/Scheduler description
https://github.com/Zeqiang-Lai/OpenDMD
Open source status
- The model implementation is available.
- The model weights are available (Only relevant if addition is not a scheduler).
Provide useful links for the implementation
No response
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the OpenDMD implementation linked in the issue and compare its One-step Diffusion with Distribution Matching Distillation model, pipeline, and scheduler components with the diffusers project. Define the integration scope and completion criteria before implementing and validating the model weights and behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100