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
| from huggingface_hub import HfApi, get_token | |
| repo_id = "AutoArk-AI/GPA" | |
| api = HfApi() | |
| try: | |
| print(f"Attempting to delete 'gpa_0_3b' from {repo_id}...") | |
| api.delete_folder(path_in_repo="gpa_0_3b", repo_id=repo_id, repo_type="model") | |
| print("Successfully deleted 'gpa_0_3b' folder from remote repository.") | |
| except Exception as e: | |
| print(f"Error deleting folder: {e}") | |