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
Upload folder using huggingface_hub
Browse files
README.md
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license: apache-2.0
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---
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<div align="center">
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<img src="figures/GPA_intro.png" width="80%" alt="GPA Logo"/>
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# GPA: One Model for Speech Recognition, Text-to-Speech, and Voice Conversion
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</div>
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license: apache-2.0
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homepage: https://autoark.github.io/GPA/
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repository: https://github.com/AutoArk/GPA
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---
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<img src="figures/GPA_intro.png" width="80%" alt="GPA Logo"/>
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# GPA: One Model for Speech Recognition, Text-to-Speech, and Voice Conversion
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[](https://github.com/AutoArk/GPA)
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</div>
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