| from diffusers import DiffusionPipeline | |
| import gradio as gr | |
| model_id = "CompVis/ldm-text2im-large-256" | |
| 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",cache_examples=False, 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) |