app.py

import gradio as gr

iface = gr.Interface.load("models/teo-sanchez/en_ner_prompting",
                          title = 'Prompt specifier recognizer by <a href="https://www.selas.ai/">Selas.ai</a>',
                          description='''<div align="center"> 
                          <a href="https://www.selas.ai">
                          <img src="https://www.selas.ai/assets/logo-selas-dark.61f4b5c4.svg" alt="Logo of selas.ai", >
                          </a>
                          <a href="https://huggingface.co/teo-sanchez/en_ner_prompting">en_ner_prompting</a>, a lightweight model recognizing the type of specifier within a text-to-image prompt.
                          </div>''',
                          examples=[["Hyperrealistic dslr film still of a cute calico cat, stunning 8 k octane comprehensive 3 d render, inspired by istvan sandorfi & greg rutkowski & unreal engine, perfect symmetry, dim volumetric cinematic lighting, extremely hyper - detailed, incredibly real lifelike attributes & flesh texture, intricate, masterpiece, artstation, stunning"],
                                    ["Quetzalcoatl in an epic battle with garuda, fantasy, stained glass, d & d, intricate, elegant, highly detailed, digital painting, artstation, concept art, matte, sharp focus, illustration, art by john collier and albert aublet and krenz cushart and artem demura and alphonse mucha"]],
                          live = True,
                          article = 'The taxonomy used for the name entity recognition is the following:\n <img src="https://storage.googleapis.com/selas-api/taxonomy.png" style="width:50%; display:block; margin-left: auto; margin-right: auto">'
                          )
iface.input_components[0].label = "Copy-paste an AI prompt you'd like to analyze"
iface.output_components[0].label = "Entities recognized in the prompt"
iface.launch()