fix: save_model_card call.

app.py

@@ -9,6 +9,7 @@ This Space lets you convert KerasCV Stable Diffusion weights to a format compati
 
 ## Notes (important)
 
+* The Space downloads a couple of pre-trained weights and runs a dummy inference. Depending, on the machine type, the enture process can take anywhere between 2 - 5 minutes.
 * Only Stable Diffusion (v1) is supported as of now. In particular this checkpoint: [`"CompVis/stable-diffusion-v1-4"`](https://huggingface.co/CompVis/stable-diffusion-v1-4).
 * Only the text encoder and the UNet parameters converted since only these two elements are generally fine-tuned.
 * [This Colab Notebook](https://colab.research.google.com/drive/1RYY077IQbAJldg8FkK8HSEpNILKHEwLb?usp=sharing) was used to develop the conversion utilities initially.
@@ -33,7 +34,6 @@ def run(hf_token, text_encoder_weights, unet_weights, repo_prefix):
         base_model=PRETRAINED_CKPT,
         repo_folder=output_path,
         weight_paths=[text_encoder_weights, unet_weights],
-        repo_prefix=repo_prefix,
     )
     push_str = push_to_hub(hf_token, output_path, repo_prefix)
     return push_str