| import gradio as gr | |
| #from transformers import pipeline | |
| from transformers import AutoModel | |
| #pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog") | |
| model = AutoModel.from_pretrained("deepsynthbody/deepfake_ecg", trust_remote_code=True) | |
| def predict(num_ecgs): | |
| predictions = model(int(num_ecgs)) | |
| return {"ecgs": predictions} | |
| gr.Interface( | |
| predict, | |
| inputs="text", | |
| outputs="text", | |
| title="Generating ECGs", | |
| ).launch() | |