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:
- 70ae9f42caf5ce6b8ea0fa49dadc7905f70025b276bc2dd2abf33efcb2531278
- Size of remote file:
- 578 MB
- SHA256:
- 4afb1e236781c447d488469aaf3045567d4d702679f15747b77ab346484d21cf
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