Adding examples and updating description

app.py

@@ -1,5 +1,4 @@
 import logging
-import os
 
 import gradio as gr
 import keras_cv
@@ -17,9 +16,8 @@ logger.info(f'Loading text encoder from: "{text_encoder_url}"')
 
 stable_diffusion = keras_cv.models.StableDiffusion()
 stable_diffusion.tokenizer.add_tokens(prompt_token)
-# loaded_text_encoder_ = tf.keras.models.load_model(text_encoder_path)
-loaded_text_encoder_ = from_pretrained_keras(text_encoder_url)
-stable_diffusion._text_encoder = loaded_text_encoder_
+text_encoder = from_pretrained_keras("Dimitre/stablediffusion-canarinho_pistola")
+stable_diffusion._text_encoder = text_encoder
 stable_diffusion._text_encoder.compile(jit_compile=True)
 
 
@@ -33,7 +31,7 @@ def generate_fn(input_prompt: str) -> np.ndarray:
         np.ndarray: Generated image
     """
     generated = stable_diffusion.text_to_image(
-        prompt=input_prompt, batch_size=1, num_steps=1
+        prompt=input_prompt, batch_size=1, num_steps=50
     )
     return generated[0]
 
@@ -41,7 +39,7 @@ def generate_fn(input_prompt: str) -> np.ndarray:
 iface = gr.Interface(
     fn=generate_fn,
     title="Textual Inversion",
-    description="Textual Inversion Demo",
+    description=f'Textual Inversion Demo, use "{prompt_token}" as the textual inversion token as shown in the examples',
     article="Note: Keras-cv uses lazy intialization, so the first use will be slower while the model is initialized.",
     inputs=gr.Textbox(
         label="Prompt",
@@ -51,6 +49,10 @@ iface = gr.Interface(
         elem_id="input-prompt",
     ),
     outputs=gr.Image(),
+    examples=[
+        ["A {prompt_token} drinking beer, 4k, highly detailed, highest quality, 8k"],
+        ["A {prompt_token} portrait, 4k, highly detailed, highest quality, 8k"],
+        ],
 )
 
 if __name__ == "__main__":