Demo of fine‑tuning Orpheus 3B on a TTS dataset in Transformer Lab
Run the demo to fine‑tune Orpheus‑3B‑0.1‑ft on a TTS dataset using Transformer Lab by connecting compute, loading campwill/HAL‑9000‑Speech, training, and sampling audio.
Run the demo to fine‑tune Orpheus‑3B‑0.1‑ft on a TTS dataset using Transformer Lab.
Summary
Transformer Lab, an open‑source ML research platform, released a demo showing how to fine‑tune the Orpheus‑3B‑0.1‑ft model on a text‑to‑speech dataset. The demo walks through connecting local compute, loading the campwill/HAL‑9000‑Speech dataset, training the model, and sampling audio from the trained weights. Both a GUI and an agent‑friendly CLI are demonstrated, and the process can be replicated on any hardware that supports a local provider. Evaluation is performed against the bosonai/EmergentTTS‑Eval dataset to benchmark quality. All resources are free and open‑source, with documentation at www.lab.cloud and the GitHub repository at github.com/transformerlab.
Key changes
- Fine‑tune Orpheus‑3B‑0.1‑ft on campwill/HAL‑9000‑Speech via Transformer Lab
- GUI and CLI support for compute connection, dataset loading, training, and audio sampling
- Integration with local provider for on‑prem hardware
- Evaluation using bosonai/EmergentTTS‑Eval dataset
- Open‑source platform with docs at www.lab.cloud and GitHub repo