Update app.py

app.py

@@ -36,26 +36,6 @@ from huggingface_hub import hf_hub_download
 #@markdown Enter the `repo_id` for a concept you like (you can find pre-learned concepts in the public [SD Concepts Library](https://huggingface.co/sd-concepts-library))
 repo_id_embeds = "sd-concepts-library/mikako-methodi2i" #@param {type:"string"}
 
-
-#@markdown (Optional) in case you have a `learned_embeds.bin` file and not a `repo_id`, add the path to `learned_embeds.bin` to the `embeds_url` variable 
-embeds_url = "" #Add the URL or path to a learned_embeds.bin file in case you have one
-placeholder_token_string = "" #Add what is the token string in case you are uploading your own embed
-
-downloaded_embedding_folder = "./downloaded_embedding"
-if not os.path.exists(downloaded_embedding_folder):
-  os.mkdir(downloaded_embedding_folder)
-if(not embeds_url):
-  embeds_path = hf_hub_download(repo_id=repo_id_embeds, filename="learned_embeds.bin", use_auth_token=True)
-  token_path = hf_hub_download(repo_id=repo_id_embeds, filename="token_identifier.txt", use_auth_token=True)
-  with open(f'{downloaded_embedding_folder}/token_identifier.txt', 'r') as file:
-    placeholder_token_string = file.read()
-else:
-  !wget -q -O $downloaded_embedding_folder/learned_embeds.bin $embeds_url
-
-learned_embeds_path = f"{downloaded_embedding_folder}/learned_embeds.bin"
-
-display (Markdown("## The placeholder token for your concept is `%s`"%(placeholder_token_string)))
-
 def image_grid(imgs, rows, cols):
     assert len(imgs) == rows*cols