1 dépôt
Awesome GitHub RepositoriesParallel Diffusion Generation
Runs multiple independent diffusion processes concurrently on the GPU to generate several outputs simultaneously.
Distinct from Parallel Batch Processing: Distinct from Parallel Batch Processing: focuses on concurrent diffusion model inference for music generation, not general data processing batching.
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Awesome Parallel Diffusion Generation GitHub Repositories
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- ace-step/ace-step-1.5
ace-step/ACE-Step-1.5
6,002Voir sur GitHubACE Step 1.5 is a local text-to-music generation and audio editing system that runs on consumer hardware. It transforms plain-language descriptions into full-length songs with lyrics, and can edit existing audio through cover generation, vocal removal, track separation, and selective repainting. The system supports multilingual prompts and lyrics in over 50 languages, and provides precise control over musical structure including duration, BPM, key, and time signature. The project distinguishes itself through a dual-stream diffusion architecture that processes separate latent streams for vocal
Generates multiple songs simultaneously by running independent diffusion processes in parallel on the GPU, maximising throughput for batch workflows.
Python
