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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, torch_dtype=torch.float16) | |
pipe = pipe.to("mps") | |
def predict(text): | |
# Ensure pipe(text) returns the correct output format | |
generated_image = pipe(text).images[0] | |
return generated_image | |
iface = gr.Interface( | |
fn=predict, | |
inputs='text', | |
outputs='image', | |
) | |
iface.launch() | |