facebook/multilingual_librispeech
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How to use semaj83/speecht5_finetuned_multilingual_librispeech_de with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-to-speech", model="semaj83/speecht5_finetuned_multilingual_librispeech_de") # Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("semaj83/speecht5_finetuned_multilingual_librispeech_de")
model = AutoModelForTextToSpectrogram.from_pretrained("semaj83/speecht5_finetuned_multilingual_librispeech_de")This model is a fine-tuned version of microsoft/speecht5_tts on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4472 | 76.92 | 1000 | 0.4305 |
| 0.4181 | 153.85 | 2000 | 0.4299 |
| 0.4138 | 230.77 | 3000 | 0.4353 |
| 0.4163 | 307.69 | 4000 | 0.4373 |
Base model
microsoft/speecht5_tts