Text-to-Speech
Transformers
Safetensors
PyTorch
English
Chinese
breeze
text-generation
speech-generation
voice-clone
voice-design
voice-direction
cuda
Instructions to use BreezeBlue/Breeze-TTS-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BreezeBlue/Breeze-TTS-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="BreezeBlue/Breeze-TTS-2")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("BreezeBlue/Breeze-TTS-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d244d21c34c21fd882a5645f7e1b77a47b283714de4a4cc6a4f8f8aa7f5e3a9f
- Size of remote file:
- 33.4 MB
- SHA256:
- d3ec9ac3eb2392389b9f5112e85d8b43316494addb587ba7b7a9d61eac23af96
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.