Update README.md

README.md

@@ -2,6 +2,8 @@
 library_name: diffusers
 tags:
 - pruna-ai
+base_model:
+- black-forest-labs/FLUX.1-Canny-dev
 ---
 
 # Model Card for PrunaAI/FLUX.1-Canny-dev-smashed
@@ -13,7 +15,7 @@ This model was created using the [pruna](https://github.com/PrunaAI/pruna) libra
 First things first, you need to install the pruna library:
 
 ```bash
-pip install pruna
+pip install pruna controlnet_aux
 ```
 
 You can [use the diffusers library to load the model](https://huggingface.co/PrunaAI/FLUX.1-Canny-dev-smashed?library=diffusers) but this might not include all optimizations by default.
@@ -23,9 +25,30 @@ To ensure that all optimizations are applied, use the pruna library to load the
 ```python
 from pruna import PrunaModel
 
-loaded_model = PrunaModel.from_hub(
+import torch
+from controlnet_aux import CannyDetector
+from diffusers import FluxControlPipeline
+from diffusers.utils import load_image
+
+pipe = PrunaModel.from_hub(
     "PrunaAI/FLUX.1-Canny-dev-smashed"
 )
+
+prompt = "A robot made of exotic candies and chocolates of different kinds. The background is filled with confetti and celebratory gifts."
+control_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/robot.png")
+
+processor = CannyDetector()
+control_image = processor(control_image, low_threshold=50, high_threshold=200, detect_resolution=1024, image_resolution=1024)
+
+image = pipe(
+    prompt=prompt,
+    control_image=control_image,
+    height=1024,
+    width=1024,
+    num_inference_steps=50,
+    guidance_scale=30.0,
+).images[0]
+image.save("output.png")
 ```
 
 After loading the model, you can use the inference methods of the original model. Take a look at the [documentation](https://pruna.readthedocs.io/en/latest/index.html) for more usage information.