A new lightweight model to do machine translation from English to Ukrainian using recently published LFM2 model. Use demo Yehor/en-uk-translator to test it.
Facts: - Fine-tuned with 40M samples (filtered by quality metric) from ~53.5M for 1.4 epochs - 354M params - Requires 1 GB of RAM to run with bf16 - BLEU on FLORES-200: 27.24 - Tokens per second: 229.93 (bs=1), 1664.40 (bs=10), 8392.48 (bs=64) - License: lfm1.0
Published a stable version of Ukrainian Text-to-Speech library on GitHub and PyPI.
Features:
- Multi-speaker model: 2 female (Tetiana, Lada) + 1 male (Mykyta) voices; - Fine-grained control over speech parameters, including duration, fundamental frequency (F0), and energy; - High-fidelity speech generation using the RAD-TTS++ acoustic model; - Fast vocoding using Vocos; - Synthesizes long sentences effectively; - Supports a sampling rate of 44.1 kHz; - Tested on Linux environments and Windows/WSL; - Python API (requires Python 3.9 or later); - CUDA-enabled for GPU acceleration.