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| import gradio as gr | |
| GK=0 | |
| from transformers import AutoTokenizer,VitsModel | |
| import torch | |
| token=os.environ.get("key_") | |
| tokenizer = AutoTokenizer.from_pretrained("wasmdashai/vits-ar-sa-huba",token=token) | |
| #device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| model_vits=VitsModel.from_pretrained("wasmdashai/vits-ar-sa-huba",token=token)#.to(device) | |
| def greet(name): | |
| global GK | |
| while True: | |
| GK+=1 | |
| model_vits=VitsModel.from_pretrained("wasmdashai/vits-ar-sa-huba",token=token)#.to(device) | |
| yield f"namber is {GK}" | |
| demo = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| demo.launch() | |