Update app.py

app.py

@@ -6,12 +6,12 @@ iface = gr.Interface.load("models/teo-sanchez/en_ner_prompting",
                           <a href="https://www.selas.ai">
                           <img src="https://www.selas.ai/assets/logo-selas-dark.61f4b5c4.svg" alt="Logo of selas.ai", >
                           </a>
-                          Lightweight model that recognize the type of specifiers within a prompt for text-to-image generation.
+                          [en_ner_prompting](https://huggingface.co/teo-sanchez/en_ner_prompting), 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 = '<img src="https://storage.googleapis.com/selas-api/taxonomy.png" style="width:30%;">'
+                          article = 'The taxonomy used for the name enntity recognition is the following:\n <img src="https://storage.googleapis.com/selas-api/taxonomy.png" style="width:30%;">'
                           )
 iface.input_components[0].label = "Copy-paste an AI prompt you'd like to analyze"
 iface.output_components[0].label = "Entity recognized in the prompt"