Update app.py

app.py

@@ -1,7 +1,4 @@
-import json
-
 import streamlit as st
-from huggingface_hub import hf_hub_download
 from utils import carga_modelo, genera
 
 ## Página principal
@@ -16,46 +13,8 @@ st.sidebar.image("assets/logo.png", width=200)
 st.sidebar.caption("Demo creado en vivo.")
 
 ## Cargamos el modelo
-model_id = "ceyda/butterfly_cropped_uniq1K_512"
-CONFIG_NAME = "config.json"
-revision = None
-cache_dir = None
-force_download = False
-proxies = None
-resume_download = False
-local_files_only = False
-token = None
-
-
-# Load the config
-config_file = hf_hub_download(
-    repo_id=str(model_id),
-    filename=CONFIG_NAME,
-    revision=revision,
-    cache_dir=cache_dir,
-    force_download=force_download,
-    proxies=proxies,
-    resume_download=resume_download,
-    token=token,
-    local_files_only=local_files_only,
-)
-with open(config_file, "r", encoding="utf-8") as f:
-    config = json.load(f)
-
-# Call the _from_pretrained with all the needed arguments
-gan = LightweightGAN()._from_pretrained(
-    model_id=str(model_id),
-    revision=revision,
-    cache_dir=cache_dir,
-    force_download=force_download,
-    proxies=proxies,
-    resume_download=resume_download,
-    local_files_only=local_files_only,
-    token=token,
-    use_auth_token=False,
-    config=config,  # usually in **model_kwargs
-)
-modelo_gan = carga_modelo(model_id)
+repo_id = "ceyda/butterfly_cropped_uniq1K_512"
+modelo_gan = carga_modelo(repo_id)
 
 # Numero de mariposas a generar
 n_mariposas = 4
@@ -82,4 +41,3 @@ if ims is not None:
     for j, im in enumerate(ims):
         i = j % n_mariposas
         cols[i].image(im, use_column_width=True)
-