Instructions to use RamWithAPlan/speecht5_tts_voxpopuli_nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RamWithAPlan/speecht5_tts_voxpopuli_nl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="RamWithAPlan/speecht5_tts_voxpopuli_nl")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("RamWithAPlan/speecht5_tts_voxpopuli_nl") model = AutoModelForTextToSpectrogram.from_pretrained("RamWithAPlan/speecht5_tts_voxpopuli_nl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b208fcfd6daa63f2b46908f2d0ce394ab45c0f6db8b4f86abe2e2a16b48de31
- Size of remote file:
- 585 MB
- SHA256:
- 21b55c3c0adc3ddfb37b9fad31e61140cbf6574ce26dde51d815dc449da0ed7d
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