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 AutoArk-AI/GPA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AutoArk-AI/GPA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="AutoArk-AI/GPA", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AutoArk-AI/GPA", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("AutoArk-AI/GPA", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9ee63557ec116b72de5770101d340e1c1d791c2566713ee3457efbbde2768fc
- Size of remote file:
- 626 MB
- SHA256:
- e9940cd48d4446e4340ced82d234bf5618350dd9f5db900ebe47a4fdb03867ec
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