---
license: mit
language:
- en
base_model:
- ZDisket/echolancer-v0.1-base
pipeline_tag: text-to-speech
---

# Echolancer-v0.1-zs

This is a TTS model trained on approximately ~5-7k hours of private labeled data, finetuned from [the base model](https://huggingface.co/ZDisket/echolancer-v0.1-base); it's conditioned on [SpeechBrain ECAPA](https://huggingface.co/speechbrain/spkrec-ecapa-voxceleb) embeddings.
This model has 177M parameters and on single AMD Instinct MI300X with the ROCm PyTorch Training v25.7 container, fine-tuning for 52k steps -- almost one epoch -- took a little under 4 hours. It's capable of zero-shot voice cloning with a reference clip

The training objective was standard next-token prediction on concatenated text-audio tokens.

# Code
For more information including a Colab notebook, see [the repository](https://github.com/ZDisket/Echolancer).