Maksym Klishch
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README.md
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- common_voice
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language:
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- uk
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---
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This model is a fine-tuned version of SpeechT5 for the Ukrainian language, using the Common Voice dataset.
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## Usage:
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```python
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!pip install git+https://github.com/huggingface/transformers
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from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5ForSpeechToSpeech, SpeechT5HifiGan
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speaker_embeddings = 2 * torch.rand((1, 512)) - 1
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text = """ pryvit yak spravy """
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speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, output_cross_attentions=True)
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waveform = vocoder.forward(speech[0])
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```
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- common_voice
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language:
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- uk
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license: mit
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base_mode: microsoft/speecht5_tts
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pipeline_tag: text-to-speech
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---
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This model is a fine-tuned version of SpeechT5 for the Ukrainian language, using the Common Voice dataset.
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## Usage:
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```python
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!pip install git+https://github.com/huggingface/transformers
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from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5ForSpeechToSpeech, SpeechT5HifiGan
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speaker_embeddings = 2 * torch.rand((1, 512)) - 1
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text = """ pryvit yak spravy """
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inputs = processor(text=text, return_tensors="pt")
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speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, output_cross_attentions=True)
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waveform = vocoder.forward(speech[0])
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```
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