diffusers and audio-diffusion-pytorch
Diffusers is a general-purpose diffusion framework that audio-diffusion-pytorch builds upon, making them complements rather than competitors—the latter provides specialized audio generation implementations compatible with the former's architecture.
About diffusers
huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
This library helps developers and researchers create or use AI models that generate new images, audio, or even molecular structures. You provide text descriptions or existing data, and it outputs novel visual, auditory, or structural content. It's designed for machine learning practitioners and AI artists.
About audio-diffusion-pytorch
archinetai/audio-diffusion-pytorch
Audio generation using diffusion models, in PyTorch.
This is a comprehensive toolkit for anyone working with audio generation using advanced AI models. You can create new audio from scratch, generate audio based on text descriptions, or enhance existing low-quality audio. It takes in audio waveforms or text prompts and outputs high-quality, synthesized audio, making it useful for sound designers, music producers, or researchers in audio AI.
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