--- license: apache-2.0 language: - en tags: - ai - rvc - vc - voice-cloning - applio - titan - pretrained datasets: - blaise-tk/TITAN-Medium pipeline_tag: audio-to-audio --- # TITAN: A Versatile, Robust, and High-Quality Pretrained Model for Retrieval-based Voice Conversion (RVC) Training ## Overview TITAN is a state-of-the-art pretrained model designed for Retrieval-based Voice Conversion (https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/) training. It offers a robust solution for transforming voice characteristics from one speaker to another, providing high-quality results with minimal training effort. ## Model Details ### Titan-Medium - Training Environment: Utilized a RTX 3060 TI on Applio v3.1.1 (https://github.com/IAHispano/Applio), employing a batch size of 8 over a span of 3 weeks. - Iterations (40k): 1010588 Steps and 467 Epochs - Iterations (32k): 1001469 Steps and 463 Epochs - Sampling rate: 48k (still training), 40k, 32k - Fine-tuning Process: RVC v2 pretrained with pitch guidance, leveraging an 11.15-hour dataset sourced from Expresso (https://arxiv.org/abs/2308.05725) also available on [datasets/blaise-tk/TITAN-Medium](https://huggingface.co/datasets/blaise-tk/TITAN-Medium). #### Samples *Tests performed with a premature ckpt at ~700k steps doing all tests under the same conditions.*
Titan-Medium Ov2 Ov2.1
### Titan-Large - Details forthcoming... ## Collaborators We appreciate the contributions of our collaborators who have helped in the development and refinement of TITAN. - Mustar - SimplCup - UnitedShoes ## Beta Testers We extend our gratitude to the beta testers who provided valuable feedback during the testing phase of TITAN. - SimplCup - Leo_Frixi - Light - SCRFilms - Ryanz - Litsa_the_dancer ## Citation Should you find TITAN beneficial for your research endeavors or projects, we kindly request citing our repository: ``` @article{titan, title={TITAN: A Versatile, Robust, and High-Quality Pretrained Model for Retrieval-based Voice Conversion (RVC) Training}, author={Blaise}, journal={Hugging Face}, year={2024}, publisher={Blaise}, url={https://huggingface.co/blaise-tk/TITAN/} } ```