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| #### text to Image on Gradio UI | |
| import torch | |
| from diffusers import DiffusionPipeline | |
| import gradio as gr | |
| # Provide the file path to your locally stored model file | |
| model_file_path = "/model/file/path/to/model/directory/" | |
| # Provide the url to model id | |
| url = "runwayml/stable-diffusion-v1-5" | |
| # Load the safetensor model | |
| pipe = DiffusionPipeline.from_pretrained(url) | |
| # Metal performance shader(mps) to optimize infernece using Mac built-in gpu : pipe = pipe.to("mps") | |
| def predict(text): | |
| # Ensure pipe(text) returns the correct output format | |
| generated_image = pipe(text).images[0] | |
| return generated_image | |
| demo = gr.Interface( | |
| fn=predict, | |
| inputs='text', | |
| outputs='image', | |
| ) | |
| demo.launch(server_name="0.0.0.0", server_port=7000) | |