Text-to-Speech
Transformers
PyTorch
TensorBoard
Safetensors
speecht5
text-to-audio
Generated from Trainer
Instructions to use Sagicc/speecht5_finetuned_multilingual_librispeech_pl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/speecht5_finetuned_multilingual_librispeech_pl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Sagicc/speecht5_finetuned_multilingual_librispeech_pl")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Sagicc/speecht5_finetuned_multilingual_librispeech_pl") model = AutoModelForTextToSpectrogram.from_pretrained("Sagicc/speecht5_finetuned_multilingual_librispeech_pl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3fe72594cf2753bd4b4baf99c99aaf44a8d4c3d53dd4477d71fa34f653091b6
- Size of remote file:
- 578 MB
- SHA256:
- f8cada4527f022af0a91275ce5a927915b4d93adbc3e7a60d21641ccb7ad0367
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