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 Edge0/GPA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Edge0/GPA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Edge0/GPA", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Edge0/GPA", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("Edge0/GPA", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Edge0/GPA: direct link, hf CLI and curl.
- Browser
- Download file 5.41 MB
-
https://huggingface.co/Edge0/GPA/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Edge0/GPA/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Edge0/GPA/resolve/main/tokenizer_config.json
5.41 MB
File too large to display, you can check the raw version instead.