Wan2.2-S2V-14B is a Mixture of Experts (MoE) model designed for audio-driven cinema-level video generation. It can generate high-quality video content based on input audio, reference images, and text prompts, supports 480P and 720P resolutions, and features complex motion generation and cinema-level aesthetic effects.

MultimodalDiffusersSpanish

ACE-Step-v1-3.5B is a text-to-audio model that supports high-quality audio generation, suitable for music and sound effects creation.

Audio ProcessingGguf

The SICTO Vocal Separator is a high-quality vocal separation model developed based on the PyTorch framework, specifically designed to extract clear vocal parts from music audio. This model is trained on the musdb18hq dataset and can provide professional-level vocal separation effects for music production and audio editing.

Audio ProcessingSafetensorsEnglish

MAGNeT is a non-autoregressive Transformer-based text-to-music and sound effects generation model capable of producing high-quality audio samples from text descriptions.

TANGO is a latent diffusion model-based text-to-audio generation tool capable of producing realistic audio including human voices, animal sounds, and natural/artificial sound effects based on text prompts.

Audio ProcessingTransformersEnglish

TANGO is an instruction-guided diffusion model for text-to-audio generation, capable of producing realistic audio including human voices, animal sounds, and natural or artificial sound effects based on text prompts.

Audio ProcessingTransformersEnglish