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from diffusers import DiffusionPipeline | |
import gradio as gr | |
model_id = "CompVis/ldm-text2im-large-256" | |
# load text input to diffusion pipeline | |
ldm = DiffusionPipeline.from_pretrained(model_id) | |
def generate_image(Prompt): | |
images = ldm([Prompt], num_inference_steps=50, eta=.3, guidance_scale=6) | |
return images.images[0] | |
interface = gr.Interface(fn = generate_image,inputs = "text",outputs = "image",title = "Mashdemy Demo Image Generator App", description = "Type in a text and click submit to generate an image:", examples = ["a clown reading a book", "a cat using a laptop", "An elephant on grass"]) | |
interface.launch(share = True) |