Instructions to use GlowLED/speecht5-voxpopuli-nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GlowLED/speecht5-voxpopuli-nl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="GlowLED/speecht5-voxpopuli-nl")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("GlowLED/speecht5-voxpopuli-nl") model = AutoModelForTextToSpectrogram.from_pretrained("GlowLED/speecht5-voxpopuli-nl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
speecht5-voxpopuli-nl
Fine-tuned microsoft/speecht5_tts on the VoxPopuli Dutch subset (7433 train / 826 test). eval_loss 0.457. For inference also load microsoft/speecht5_hifigan as vocoder and supply a speaker embedding via SpeechT5ForTextToSpeech.generate_speech.
Metrics
- training loss converged
Usage
# text-to-speech
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