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.ipynb_checkpoints/app-checkpoint.py

@@ -25,7 +25,7 @@ magic_model.decoder.compile(jit_compile=True)
 magic_model.text_encoder.compile(jit_compile=True)
 
 # Warm-up the model
-_ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen)
+_ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen, num_steps=15)
 
 def generate_image_fn(prompt: str, steps: int) -> list:
     start_time = time.time()
@@ -43,7 +43,7 @@ def generate_image_fn(prompt: str, steps: int) -> list:
     return [image for image in images]
 
 
-description = "This Space demonstrates a fine-tuned Stable Diffusion model. You can use it for generating custom Magic the Gathering cards. To get started, either enter a prompt or pick one from the examples below. For details on the fine-tuning procedure, refer to [this repository](https://gpuopen.com/)."
+description = "This Space demonstrates a fine-tuned Stable Diffusion model. You can use it for generating custom Magic the Gathering cards. To get started, either enter a prompt or pick one from the examples below. For details on the fine-tuning procedure, refer to [this tutorial](https://gpuopen.com/)."
 article = "We use mixed-precision and XLA to speed up the inference latency."
 gr.Interface(
     generate_image_fn,
@@ -53,12 +53,12 @@ gr.Interface(
             max_lines=1,
             placeholder="Jedi",
         ),
-        gr.Slider(value=70, minimum=10, maximum=100, step=1),
+        gr.Slider(value=30, minimum=10, maximum=100, step=1),
     ],
-    outputs=gr.Gallery().style(grid=[2], height="auto"),
+    outputs=gr.Gallery().style(height="auto"),
     title="Generate custom magic the gathering cards",
     description=description,
     article=article,
-    examples=[["Yoda", 70], ["Lisa Su", 70]],
+    examples=[["Yoda", 30], ["Lisa Su", 30]],
     allow_flagging=False,
 ).launch(enable_queue=True)

.ipynb_checkpoints/constants-checkpoint.py

@@ -122,7 +122,7 @@ css = """
         .image_duplication{position: absolute; width: 100px; left: 50px}
 """
 
-num_images_to_gen = 3
+num_images_to_gen = 1
 unconditional_guidance_scale = 30
 img_height = 512
 img_width = 512

app.py

@@ -25,7 +25,7 @@ magic_model.decoder.compile(jit_compile=True)
 magic_model.text_encoder.compile(jit_compile=True)
 
 # Warm-up the model
-_ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen)
+_ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen, num_steps=15)
 
 def generate_image_fn(prompt: str, steps: int) -> list:
     start_time = time.time()
@@ -43,7 +43,7 @@ def generate_image_fn(prompt: str, steps: int) -> list:
     return [image for image in images]
 
 
-description = "This Space demonstrates a fine-tuned Stable Diffusion model. You can use it for generating custom Magic the Gathering cards. To get started, either enter a prompt or pick one from the examples below. For details on the fine-tuning procedure, refer to [this repository](https://gpuopen.com/)."
+description = "This Space demonstrates a fine-tuned Stable Diffusion model. You can use it for generating custom Magic the Gathering cards. To get started, either enter a prompt or pick one from the examples below. For details on the fine-tuning procedure, refer to [this tutorial](https://gpuopen.com/)."
 article = "We use mixed-precision and XLA to speed up the inference latency."
 gr.Interface(
     generate_image_fn,
@@ -53,12 +53,12 @@ gr.Interface(
             max_lines=1,
             placeholder="Jedi",
         ),
-        gr.Slider(value=70, minimum=10, maximum=100, step=1),
+        gr.Slider(value=30, minimum=10, maximum=100, step=1),
     ],
-    outputs=gr.Gallery().style(grid=[2], height="auto"),
+    outputs=gr.Gallery().style(height="auto"),
     title="Generate custom magic the gathering cards",
     description=description,
     article=article,
-    examples=[["Yoda", 70], ["Lisa Su", 70]],
+    examples=[["Yoda", 30], ["Lisa Su", 30]],
     allow_flagging=False,
 ).launch(enable_queue=True)

constants.py

@@ -122,7 +122,7 @@ css = """
         .image_duplication{position: absolute; width: 100px; left: 50px}
 """
 
-num_images_to_gen = 3
+num_images_to_gen = 1
 unconditional_guidance_scale = 30
 img_height = 512
 img_width = 512