custom-diffusion-space

README.md

@@ -7,7 +7,6 @@ sdk: gradio
 sdk_version: 3.12.0
 app_file: app.py
 pinned: false
-license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,9 +1,8 @@
 #!/usr/bin/env python
-"""Unofficial demo app for https://github.com/adobe-research/custom-diffusion.
+"""Demo app for https://github.com/adobe-research/custom-diffusion.
 
 The code in this repo is partly adapted from the following repository:
 https://huggingface.co/spaces/hysts/LoRA-SD-training
-The license of the original code is MIT, which is specified in the README.md.
 """
 
 from __future__ import annotations
@@ -176,7 +175,7 @@ def create_inference_demo(pipe: InferencePipeline) -> gr.Blocks:
                                  minimum=0,
                                  maximum=100000,
                                  step=1,
-                                 value=1)
+                                 value=42)
                 with gr.Accordion('Other Parameters', open=False):
                     num_steps = gr.Slider(label='Number of Steps',
                                           minimum=0,

inference.py

@@ -14,7 +14,6 @@ sys.path.insert(0, 'custom-diffusion')
 
 
 def load_model(text_encoder, tokenizer, unet, save_path, modifier_token, freeze_model='crossattn_kv'):
-    logger.info("loading embeddings")
     st = torch.load(save_path)
     if 'text_encoder' in st:
         text_encoder.load_state_dict(st['text_encoder'])