Text-to-Speech
Transformers
Safetensors
English
gemma
text-generation
tts
neucodec
audio-generation
research
speech-synthesis
text-generation-inference
Instructions to use BlandAI/BeigeTTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BlandAI/BeigeTTS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="BlandAI/BeigeTTS")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BlandAI/BeigeTTS") model = AutoModelForCausalLM.from_pretrained("BlandAI/BeigeTTS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8bd537e81d8f1e5bd1006d52dd9ad6f4ddde2f9c218b9127d615d5f85f67ae2
- Size of remote file:
- 33.4 MB
- SHA256:
- 1cfdfbadc2cef8f5558377a4bf7ad30da3c6af4618164efdbb4c96ea31e72cd1
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