change base model

gui.py

@@ -1,18 +1,16 @@
 import spaces
 import os
-from stablepy import Model_Diffusers
 import torch
 import logging
 import random
 import gradio as gr
-
+import diffusers
 from models.upscaler import upscaler_dict_gui
+from stablepy import Model_Diffusers
+from utils.download_utils import download_things
 
 logging.getLogger("diffusers").setLevel(logging.ERROR)
-import diffusers
-
 diffusers.utils.logging.set_verbosity(40)
-from utils.download_utils import download_things
 
 hf_token: str = os.environ.get("HF_TOKEN")
 
@@ -28,7 +26,7 @@ class GuiSD:
 
         print("Loading model...")
         self.model = Model_Diffusers(
-            base_model_id="cagliostrolab/animagine-xl-3.1",
+            base_model_id="models/animaPencilXL_v500.safetensors",
             task_name="txt2img",
             vae_model=None,
             type_model_precision=torch.float16,
@@ -60,7 +58,12 @@ class GuiSD:
             model_is_xl = "xl" in model_name.lower()
             sdxl_in_vae = vae_model and "sdxl" in vae_model.lower()
             model_type = "SDXL" if model_is_xl else "SD 1.5"
-            incompatible_vae = (model_is_xl and vae_model and not sdxl_in_vae) or (not model_is_xl and sdxl_in_vae)
+            incompatible_vae = ((
+                                        model_is_xl and
+                                        vae_model and
+                                        not sdxl_in_vae) or
+                                (not model_is_xl and
+                                 sdxl_in_vae))
 
             if incompatible_vae:
                 vae_model = None
@@ -210,7 +213,7 @@ class GuiSD:
                 print(la)
                 lora_type = ("animetarot" in la.lower() or "Hyper-SD15-8steps".lower() in la.lower())
                 if (model_is_xl and lora_type) or (not model_is_xl and not lora_type):
-                    msg_inc_lora = f"The LoRA {la} is for {'SD 1.5' if model_is_xl else 'SDXL'}, but you are using {model_type}."
+                    msg_inc_lora = f'The LoRA {la} is for {'SD 1.5' if model_is_xl else 'SDXL'}, but you are using {model_type}.'
                     gr.Info(msg_inc_lora)
                     msg_lora.append(msg_inc_lora)
 
@@ -223,8 +226,16 @@ class GuiSD:
         params_ip_scale: list = []
 
         all_adapters = [
-            (image_ip1, mask_ip1, model_ip1, mode_ip1, scale_ip1),
-            (image_ip2, mask_ip2, model_ip2, mode_ip2, scale_ip2),
+            (image_ip1,
+             mask_ip1,
+             model_ip1,
+             mode_ip1,
+             scale_ip1),
+            (image_ip2,
+             mask_ip2,
+             model_ip2,
+             mode_ip2,
+             scale_ip2),
         ]
 
         for (imgip,
@@ -263,11 +274,18 @@ class GuiSD:
         if task == "inpaint" and not image_mask:
             raise ValueError("No mask image found: Specify one in 'Image Mask'")
 
-        if upscaler_model_path in [None, "Lanczos", "Nearest"]:
+        if upscaler_model_path in [
+            None,
+            "Lanczos",
+            "Nearest"
+        ]:
             upscaler_model = upscaler_model_path
         else:
             directory_upscalers = 'upscalers'
-            os.makedirs(directory_upscalers, exist_ok=True)
+            os.makedirs(
+                directory_upscalers,
+                exist_ok=True
+            )
 
             url_upscaler = upscaler_dict_gui[upscaler_model_path]
 
@@ -309,7 +327,6 @@ class GuiSD:
             "inpaint_only": adetailer_inpaint_only,
             "sampler": adetailer_sampler,
         }
-
         adetailer_params_B: dict = {
             "face_detector_ad": face_detector_ad_b,
             "person_detector_ad": person_detector_ad_b,