Instructions to use hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech") model = AutoModelForTextToSpectrogram.from_pretrained("hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 272 Bytes
922e748 | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"bos_token": "<s>",
"clean_up_tokenization_spaces": true,
"eos_token": "</s>",
"model_max_length": 450,
"pad_token": "<pad>",
"processor_class": "SpeechT5Processor",
"sp_model_kwargs": {},
"tokenizer_class": "SpeechT5Tokenizer",
"unk_token": "<unk>"
}
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