Instructions to use Wsassi/speecht5_tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wsassi/speecht5_tts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Wsassi/speecht5_tts")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Wsassi/speecht5_tts") model = AutoModelForTextToSpectrogram.from_pretrained("Wsassi/speecht5_tts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ec917b3de04c59578c53b2b265d7ebb4dcccecae909b20736b62f00a2dd4a4d
- Size of remote file:
- 5.24 kB
- SHA256:
- a1679d8a2a238983330ee6ac054740334a97915f7d58a394b96ed79fe9e94bcd
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