Text-to-Speech
Transformers
PyTorch
TensorBoard
Safetensors
English
speecht5
text-to-audio
Generated from Trainer
Instructions to use Avitas8485/speecht5_tts_commonvoice_en_06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Avitas8485/speecht5_tts_commonvoice_en_06 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Avitas8485/speecht5_tts_commonvoice_en_06")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Avitas8485/speecht5_tts_commonvoice_en_06") model = AutoModelForTextToSpectrogram.from_pretrained("Avitas8485/speecht5_tts_commonvoice_en_06", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Avitas8485/speecht5_tts_commonvoice_en_06: direct link, hf CLI and curl.
- Browser
- Download file 272 Bytes
-
https://huggingface.co/Avitas8485/speecht5_tts_commonvoice_en_06/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Avitas8485/speecht5_tts_commonvoice_en_06/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Avitas8485/speecht5_tts_commonvoice_en_06/resolve/main/tokenizer_config.json
272 Bytes
| { | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "</s>", | |
| "model_max_length": 600, | |
| "pad_token": "<pad>", | |
| "processor_class": "SpeechT5Processor", | |
| "sp_model_kwargs": {}, | |
| "tokenizer_class": "SpeechT5Tokenizer", | |
| "unk_token": "<unk>" | |
| } | |