fix: formatting.

convert.py

@@ -64,7 +64,7 @@ def run_conversion(text_encoder_weights: str = None, unet_weights: str = None):
 
     text_encoder_state_dict_from_tf = populate_text_encoder(tf_text_encoder)
     unet_state_dict_from_tf = populate_unet(tf_unet)
-    print("Conversion done, now running assertions...")
+    print("Conversion done, now running optional assertions...")
 
     # Since we cannot compare the fine-tuned weights.
     if text_encoder_weights is None:
@@ -74,9 +74,10 @@ def run_conversion(text_encoder_weights: str = None, unet_weights: str = None):
         unet_state_dict_from_pt = pt_unet.state_dict()
         run_assertion(unet_state_dict_from_pt, unet_state_dict_from_tf)
 
-    print(
-        "Assertions successful, populating the converted parameters into the diffusers models..."
-    )
+    if text_encoder_weights is None or unet_weights is None:
+        print(
+            "Assertions successful, populating the converted parameters into the diffusers models..."
+        )
     pt_text_encoder.load_state_dict(text_encoder_state_dict_from_tf)
     pt_unet.load_state_dict(unet_state_dict_from_tf)
 

hub_utils/readme.py

@@ -19,7 +19,7 @@ inference: true
     model_card = f"""
 # KerasCV Stable Diffusion in Diffusers 🧨🤗
 
-The pipeline contained in this repository was created using [this Space](https://huggingface.co/spaces/sayakpaul/convert-kerascv-sd-diffusers). The purpose is to convert the KerasCV Stable Diffusion weights in a way that is compatible with Diffusers. This allows users to fine-tune using KerasCV and use the fine-tuned weights in Diffusers taking advantage of its nifty features (like schedulers, fast attention, etc.).\n
+The pipeline contained in this repository was created using [this Space](https://huggingface.co/spaces/sayakpaul/convert-kerascv-sd-diffusers). The purpose is to convert the KerasCV Stable Diffusion weights in a way that is compatible with [Diffusers](https://github.com/huggingface/diffusers). This allows users to fine-tune using KerasCV and use the fine-tuned weights in Diffusers taking advantage of its nifty features (like [schedulers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/schedulers), [fast attention](https://huggingface.co/docs/diffusers/optimization/fp16), etc.).\n
 
 """