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--- |
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license: cc-by-nc-sa-4.0 |
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datasets: |
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- openslr |
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- mozilla-foundation/common_voice_13_0 |
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- Lagos-NWU_Yoruba_Speech_Corpus |
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language: |
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- yo |
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library_name: transformers |
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pipeline_tag: text-to-speech |
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--- |
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```python |
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# Load model directly |
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from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan |
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from huggingface_hub import hf_hub_download |
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import torch |
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processor = SpeechT5Processor.from_pretrained("imhotepai/yoruba-tts") |
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model = SpeechT5ForTextToSpeech.from_pretrained("imhotepai/yoruba-tts") |
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dir_= hf_hub_download(repo_id="imhotepai/yoruba-tts", filename="speaker_embeddings.pt") |
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speaker_embeddings= torch.load(dir_) |
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text='Báwó ni'.lower() |
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inputs = processor(text=text, return_tensors="pt") |
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vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan") |
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speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder) |
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# Audio in notebook |
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from IPython.display import Audio |
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Audio(speech.numpy(), rate=16000) |
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``` |
