Deploying a generative ML model for images

The Gradio framework is very flexible and allows for quickly deploying models such as generative AI stable diffusion models – image generators that work similarly to the DALL-E model. The deployment of such a model is very similar to the deployment of the numerical model we covered previously.

First, we need to create a function that will generate images based on one of the models from Hugging Face. The following code fragment shows this function:

import gradio as gr
import pandas as pd
from diffusers import StableDiffusionPipeline
import torch
def generate_images(prompt):
    '''
    This function uses the prompt to generate an image
    using the anything 4.0 model from Hugging Face
    '''
    # importing the model from Hugging Face
    model_id = "xyn-ai/anything-v4.0"...