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
[Demo] Breeze TTS 2 will be available in audio.cpp’s dev branch for testing. 6GB VRAM 3x faster than realtime. No Python.
#5
by audio-cpp - opened
Breeze TTS 2 will be available in audio.cpp’s dev branch for testing later this week.
RTF = 0.3 on RTX 5090 (3x realtime). Longform RTF = 0.25. Peak VRAM is about 6GB.
If you’re tired of wrestling with Python environments and dependencies just to try an audio model, give audio.cpp a try!
Star or watch our repo so you don’t miss new models!
audio-cpp changed discussion title from Breeze TTS 2 will be available in audio.cpp’s dev branch for testing. 6GB VRAM 3x faster than realtime. No Python. Demo included to [Demo] Breeze TTS 2 will be available in audio.cpp’s dev branch for testing. 6GB VRAM 3x faster than realtime. No Python.