Text-to-Speech
Transformers
ONNX
Safetensors
English
Chinese
qwen3
text-generation
automatic-speech-recognition
voice-conversion
speech
audio
custom_code
text-generation-inference
Instructions to use Audio8/GPA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Audio8/GPA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Audio8/GPA", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Audio8/GPA", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("Audio8/GPA", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88c50072e95aeeae1b484a9487f3cddbc7fcf2d8c53b2ba376a56e9c7e58003e
- Size of remote file:
- 625 MB
- SHA256:
- 3b7b2c9ab7547c6ba9688d1fc3c03e587ee248a0a5a6fe441e9d687a12605a99
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