Instructions to use Bingsu/speecht5_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bingsu/speecht5_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Bingsu/speecht5_test")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Bingsu/speecht5_test") model = AutoModelForTextToSpectrogram.from_pretrained("Bingsu/speecht5_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "do_lower_case": false, | |
| "do_phonemize": true, | |
| "eos_token": "</s>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "phone_delimiter_token": " ", | |
| "phonemizer_backend": "espeak", | |
| "phonemizer_lang": "ko", | |
| "tokenizer_class": "Wav2Vec2PhonemeCTCTokenizer", | |
| "tokenizer_file": null, | |
| "unk_token": "<unk>", | |
| "word_delimiter_token": "|" | |
| } | |