Text-to-Speech
Transformers
Safetensors
PyTorch
English
Chinese
breeze
text-generation
speech-generation
voice-clone
voice-design
voice-direction
cuda
Instructions to use Coder40-95/Breeze-TTS-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Coder40-95/Breeze-TTS-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Coder40-95/Breeze-TTS-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Coder40-95/Breeze-TTS-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download audio_tokenizer/preprocessor_config.json from Coder40-95/Breeze-TTS-2: direct link, hf CLI and curl.
- Browser
- Download file 234 Bytes
-
https://huggingface.co/Coder40-95/Breeze-TTS-2/resolve/main/audio_tokenizer/preprocessor_config.json
- Command line
-
hf download hf://Coder40-95/Breeze-TTS-2/audio_tokenizer/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Coder40-95/Breeze-TTS-2/resolve/main/audio_tokenizer/preprocessor_config.json
234 Bytes
| { | |
| "chunk_length_s": null, | |
| "feature_extractor_type": "EncodecFeatureExtractor", | |
| "feature_size": 1, | |
| "overlap": null, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 24000 | |
| } | |