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:
- 31d50b79f4650d635c4953514bb49bb0bde4f0abaa3a967e51b857d5058df239
- Size of remote file:
- 407 kB
- SHA256:
- 1a3577059b2c1c4bb67b587014197f98f4d0768805afd182d44562011dd00ea2
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