Instructions to use maurorisonho/speecht5-tts-audio-course with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maurorisonho/speecht5-tts-audio-course with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="maurorisonho/speecht5-tts-audio-course")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("maurorisonho/speecht5-tts-audio-course") model = AutoModelForTextToSpectrogram.from_pretrained("maurorisonho/speecht5-tts-audio-course", device_map="auto") - Notebooks
- Google Colab
- Kaggle
SpeechT5 Neural Text-to-Speech (TTS) Model
This model is a neural text-to-speech architecture based on Microsoft SpeechT5, fine-tuned for high-fidelity voice generation as part of the Hugging Face Audio Transformers Course (Unit 6).
🚀 Model Details
- Task: Text-to-Speech (Neural Vocoding)
- Architecture: SpeechT5 with character-level SentencePiece tokenization
- Status: Officially Verified & Certified
- Downloads last month
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Evaluation results
- Lossself-reported0.150