Update README.md

README.md

@@ -2,6 +2,8 @@
 library_name: diffusers
 tags:
 - pruna-ai
+base_model:
+- black-forest-labs/FLUX.1-Depth-dev
 ---
 
 # Model Card for PrunaAI/FLUX.1-Fill-dev-smashed
@@ -14,6 +16,8 @@ First things first, you need to install the pruna library:
 
 ```bash
 pip install pruna
+pip install git+https://github.com/asomoza/image_gen_aux.git
+
 ```
 
 You can [use the diffusers library to load the model](https://huggingface.co/PrunaAI/FLUX.1-Fill-dev-smashed?library=diffusers) but this might not include all optimizations by default.
@@ -23,9 +27,31 @@ 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 diffusers import FluxControlPipeline, FluxTransformer2DModel
+from diffusers.utils import load_image
+from image_gen_aux import DepthPreprocessor
+
+pipe = PrunaModel.from_hub(
     "PrunaAI/FLUX.1-Fill-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 = DepthPreprocessor.from_pretrained("LiheYoung/depth-anything-large-hf")
+control_image = processor(control_image)[0].convert("RGB")
+
+image = pipe(
+    prompt=prompt,
+    control_image=control_image,
+    height=1024,
+    width=1024,
+    num_inference_steps=30,
+    guidance_scale=10.0,
+    generator=torch.Generator().manual_seed(42),
+).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.