Upload 4 files

app.py

@@ -8,6 +8,7 @@ from stablepy import (
     check_scheduler_compatibility,
     TASK_AND_PREPROCESSORS,
     FACE_RESTORATION_MODELS,
+    PROMPT_WEIGHT_OPTIONS_PRIORITY,
     scheduler_names,
 )
 from constants import (
@@ -398,7 +399,7 @@ class GuiSD:
         t2i_adapter_preprocessor,
         t2i_adapter_conditioning_scale,
         t2i_adapter_conditioning_factor,
-        xformers_memory_efficient_attention,
+        enable_live_preview,
         freeu,
         generator_in_cpu,
         adetailer_inpaint_only,
@@ -577,7 +578,7 @@ class GuiSD:
             "sampler": sampler,
             "schedule_type": schedule_type,
             "schedule_prediction_type": schedule_prediction_type,
-            "xformers_memory_efficient_attention": xformers_memory_efficient_attention,
+            "xformers_memory_efficient_attention": False,
             "gui_active": True,
             "loop_generation": loop_generation,
             "controlnet_conditioning_scale": float(controlnet_output_scaling_in_unet),
@@ -592,7 +593,7 @@ class GuiSD:
             "leave_progress_bar": leave_progress_bar,
             "disable_progress_bar": disable_progress_bar,
             "image_previews": image_previews,
-            "display_images": display_images,
+            "display_images": False,
             "save_generated_images": save_generated_images,
             "filename_pattern": filename_pattern,
             "image_storage_location": image_storage_location,
@@ -668,13 +669,16 @@ class GuiSD:
                 )
                 if save_generated_images:
                     info_images += f"<br>{download_links}"
-
 ## BEGIN MOD
                 img = save_images(img, metadata)
+                if not display_images:
+                    img = gr.update(value=img) if img else gr.update()
 ## END MOD
-
                 info_state = "COMPLETE"
 
+            elif not enable_live_preview:
+                img = gr.update()
+
             yield info_state, img, info_images
 
 
@@ -957,142 +961,147 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
                             vae_model_gui = gr.Dropdown(label="VAE Model", choices=vae_model_list, value=vae_model_list[0])
                             prompt_syntax_gui = gr.Dropdown(label="Prompt Syntax", choices=PROMPT_W_OPTIONS, value=PROMPT_W_OPTIONS[1][1])
 
-                        with gr.Row(equal_height=False):
-
-                            def run_set_params_gui(base_prompt, name_model):
-                                valid_receptors = {  # default values
-                                    "prompt": gr.update(value=base_prompt),
-                                    "neg_prompt": gr.update(value=""),
-                                    "Steps": gr.update(value=30),
-                                    "width": gr.update(value=1024),
-                                    "height": gr.update(value=1024),
-                                    "Seed": gr.update(value=-1),
-                                    "Sampler": gr.update(value="Euler"),
-                                    "CFG scale": gr.update(value=7.),  # cfg
-                                    "Clip skip": gr.update(value=True),
-                                    "Model": gr.update(value=name_model),
-                                    "Schedule type": gr.update(value="Automatic"),
-                                    "PAG": gr.update(value=.0),
-                                    "FreeU": gr.update(value=False),
-                                    "Hires upscaler": gr.update(),
-                                    "Hires upscale": gr.update(),
-                                    "Hires steps": gr.update(),
-                                    "Hires denoising strength": gr.update(),
-                                    "Hires CFG": gr.update(),
-                                    "Hires sampler": gr.update(),
-                                    "Hires schedule type": gr.update(),
-                                    "Image resolution": gr.update(value=1024),
-                                    "Strength": gr.update(),
-                                }
-
-                                # Generate up to 7 LoRAs
-                                for i in range(1, 8):
-                                    valid_receptors[f"Lora_{i}"] = gr.update()
-                                    valid_receptors[f"Lora_scale_{i}"] = gr.update()
-
-                                valid_keys = list(valid_receptors.keys())
-
-                                parameters = extract_parameters(base_prompt)
-                                # print(parameters)
-
-                                if "Sampler" in parameters:
-                                    value_sampler = parameters["Sampler"]
-                                    for s_type in SCHEDULE_TYPE_OPTIONS:
-                                        if s_type in value_sampler:
-                                            value_sampler = value_sampler.replace(s_type, "").strip()
-                                            parameters["Sampler"] = value_sampler
-                                            parameters["Schedule type"] = s_type
-
-                                params_lora = []
-                                if ">" in parameters["prompt"] and "<" in parameters["prompt"]:
-                                    params_lora = re.findall(r'<lora:[^>]+>', parameters["prompt"])
-                                if "Loras" in parameters:
-                                    params_lora += re.findall(r'<lora:[^>]+>', parameters["Loras"])
-
-                                if params_lora:
-                                    parsed_params = []
-                                    for tag_l in params_lora:
-                                        try:
-                                            inner = tag_l.strip("<>")        # remove < >
-                                            _, data_l = inner.split(":", 1)  # remove the "lora:" part
-                                            parts_l = data_l.split(":")
-
-                                            name_l = parts_l[0]
-                                            weight_l = float(parts_l[1]) if len(parts_l) > 1 else 1.0  # default weight = 1.0
-
-                                            parsed_params.append((name_l, weight_l))
-                                        except Exception as e:
-                                            print(f"Error parsing LoRA tag {tag_l}: {e}")
-
-                                    num_lora = 1
-                                    for parsed_l, parsed_s in parsed_params:
-                                        filtered_loras = [m for m in lora_model_list if parsed_l in m]
-                                        if filtered_loras:
-                                            parameters[f"Lora_{num_lora}"] = filtered_loras[0]
-                                            parameters[f"Lora_scale_{num_lora}"] = parsed_s
-                                            num_lora += 1
-
-                                # continue = discard new value
-                                for key, val in parameters.items():
-                                    # print(val)
-                                    if key in valid_keys:
-                                        try:
-                                            if key == "Sampler":
-                                                if val not in scheduler_names:
-                                                    continue
-                                            if key in ["Schedule type", "Hires schedule type"]:
-                                                if val not in SCHEDULE_TYPE_OPTIONS:
-                                                    continue
-                                            if key == "Hires sampler":
-                                                if val not in POST_PROCESSING_SAMPLER:
-                                                    continue
-                                            elif key == "Clip skip":
-                                                if "," in str(val):
-                                                    val = val.replace(",", "")
-                                                if int(val) >= 2:
-                                                    val = True
-                                            if key == "prompt":
-                                                if ">" in val and "<" in val:
-                                                    val = re.sub(r'<[^>]+>', '', val)  # Delete html and loras
-                                                    print("Removed LoRA written in the prompt")
-                                            if key in ["prompt", "neg_prompt"]:
-                                                val = re.sub(r'\s+', ' ', re.sub(r',+', ',', val)).strip()
-                                            if key in ["Steps", "width", "height", "Seed", "Hires steps", "Image resolution"]:
-                                                val = int(val)
-                                            if key == "FreeU":
-                                                val = True
-                                            if key in ["CFG scale", "PAG", "Hires upscale", "Hires denoising strength", "Hires CFG", "Strength"]:
-                                                val = float(val)
-                                            if key == "Model":
-                                                filtered_models = [m for m in model_list if val in m]
-                                                if filtered_models:
-                                                    val = filtered_models[0]
-                                                else:
-                                                    val = name_model
-                                            if key == "Hires upscaler":
-                                                if val not in UPSCALER_KEYS:
-                                                    continue
-                                            if key == "Seed":
-                                                continue
-
-                                            valid_receptors[key] = gr.update(value=val)
-                                            # print(val, type(val))
-                                            # print(valid_receptors)
-                                        except Exception as e:
-                                            print(str(e))
-                                return [value for value in valid_receptors.values()]
-
-                            def run_clear_prompt_gui():
-                                return gr.update(value=""), gr.update(value="")
-                            clear_prompt_gui.click(
-                                run_clear_prompt_gui, [], [prompt_gui, neg_prompt_gui], show_api=False
-                            )
+                    def run_set_params_gui(base_prompt, name_model):
+                        valid_receptors = {  # default values
+                            "prompt": gr.update(value=base_prompt),
+                            "neg_prompt": gr.update(value=""),
+                            "Steps": gr.update(value=30),
+                            "width": gr.update(value=1024),
+                            "height": gr.update(value=1024),
+                            "Seed": gr.update(value=-1),
+                            "Sampler": gr.update(value="Euler"),
+                            "CFG scale": gr.update(value=7.),  # cfg
+                            "Clip skip": gr.update(value=True),
+                            "Model": gr.update(value=name_model),
+                            "Schedule type": gr.update(value="Automatic"),
+                            "PAG": gr.update(value=.0),
+                            "FreeU": gr.update(value=False),
+                            "Hires upscaler": gr.update(),
+                            "Hires upscale": gr.update(),
+                            "Hires steps": gr.update(),
+                            "Hires denoising strength": gr.update(),
+                            "Hires CFG": gr.update(),
+                            "Hires sampler": gr.update(),
+                            "Hires schedule type": gr.update(),
+                            "Image resolution": gr.update(value=1024),
+                            "Strength": gr.update(),
+                            "Prompt emphasis": gr.update(),
+                        }
+
+                        # Generate up to 7 LoRAs
+                        for i in range(1, 8):
+                            valid_receptors[f"Lora_{i}"] = gr.update()
+                            valid_receptors[f"Lora_scale_{i}"] = gr.update()
+
+                        valid_keys = list(valid_receptors.keys())
+
+                        parameters = extract_parameters(base_prompt)
+                        # print(parameters)
+
+                        if "Sampler" in parameters:
+                            value_sampler = parameters["Sampler"]
+                            for s_type in SCHEDULE_TYPE_OPTIONS:
+                                if s_type in value_sampler:
+                                    value_sampler = value_sampler.replace(s_type, "").strip()
+                                    parameters["Sampler"] = value_sampler
+                                    parameters["Schedule type"] = s_type
+
+                        params_lora = []
+                        if ">" in parameters["prompt"] and "<" in parameters["prompt"]:
+                            params_lora = re.findall(r'<lora:[^>]+>', parameters["prompt"])
+                        if "Loras" in parameters:
+                            params_lora += re.findall(r'<lora:[^>]+>', parameters["Loras"])
+
+                        if params_lora:
+                            parsed_params = []
+                            for tag_l in params_lora:
+                                try:
+                                    inner = tag_l.strip("<>")        # remove < >
+                                    _, data_l = inner.split(":", 1)  # remove the "lora:" part
+                                    parts_l = data_l.split(":")
+
+                                    name_l = parts_l[0]
+                                    weight_l = float(parts_l[1]) if len(parts_l) > 1 else 1.0  # default weight = 1.0
+
+                                    parsed_params.append((name_l, weight_l))
+                                except Exception as e:
+                                    print(f"Error parsing LoRA tag {tag_l}: {e}")
+
+                            new_lora_model_list = get_model_list(DIRECTORY_LORAS)
+                            new_lora_model_list.insert(0, "None")
+
+                            num_lora = 1
+                            for parsed_l, parsed_s in parsed_params:
+                                filtered_loras = [m for m in new_lora_model_list if parsed_l in m]
+                                if filtered_loras:
+                                    parameters[f"Lora_{num_lora}"] = filtered_loras[0]
+                                    parameters[f"Lora_scale_{num_lora}"] = parsed_s
+                                    num_lora += 1
+
+                        # continue = discard new value
+                        for key, val in parameters.items():
+                            # print(val)
+                            if key in valid_keys:
+                                try:
+                                    if key == "Sampler":
+                                        if val not in scheduler_names:
+                                            continue
+                                    if key in ["Schedule type", "Hires schedule type"]:
+                                        if val not in SCHEDULE_TYPE_OPTIONS:
+                                            continue
+                                    if key == "Hires sampler":
+                                        if val not in POST_PROCESSING_SAMPLER:
+                                            continue
+                                    if key == "Prompt emphasis":
+                                        if val not in PROMPT_WEIGHT_OPTIONS_PRIORITY:
+                                            continue
+                                    elif key == "Clip skip":
+                                        if "," in str(val):
+                                            val = val.replace(",", "")
+                                        if int(val) >= 2:
+                                            val = True
+                                    if key == "prompt":
+                                        if ">" in val and "<" in val:
+                                            val = re.sub(r'<[^>]+>', '', val)  # Delete html and loras
+                                            print("Removed LoRA written in the prompt")
+                                    if key in ["prompt", "neg_prompt"]:
+                                        val = re.sub(r'\s+', ' ', re.sub(r',+', ',', val)).strip()
+                                    if key in ["Steps", "width", "height", "Seed", "Hires steps", "Image resolution"]:
+                                        val = int(val)
+                                    if key == "FreeU":
+                                        val = True
+                                    if key in ["CFG scale", "PAG", "Hires upscale", "Hires denoising strength", "Hires CFG", "Strength"]:
+                                        val = float(val)
+                                    if key == "Model":
+                                        filtered_models = [m for m in model_list if val in m]
+                                        if filtered_models:
+                                            val = filtered_models[0]
+                                        else:
+                                            val = name_model
+                                    if key == "Hires upscaler":
+                                        if val not in UPSCALER_KEYS:
+                                            continue
+                                    if key == "Seed":
+                                        continue
+
+                                    valid_receptors[key] = gr.update(value=val)
+                                    # print(val, type(val))
+                                    # print(valid_receptors)
+                                except Exception as e:
+                                    print(str(e))
+                        return [value for value in valid_receptors.values()]
+
+                    def run_clear_prompt_gui():
+                        return gr.update(value=""), gr.update(value="")
+                    clear_prompt_gui.click(
+                        run_clear_prompt_gui, [], [prompt_gui, neg_prompt_gui]
+                    )
 
-                            def run_set_random_seed():
-                                return -1
-                            set_random_seed.click(
-                                run_set_random_seed, [], seed_gui, show_api=False
-                            )
+                    def run_set_random_seed():
+                        return -1
+                    set_random_seed.click(
+                        run_set_random_seed, [], seed_gui
+                    )
 
                     with gr.Accordion("LoRA", open=False, visible=True) as menu_lora:
                         def lora_dropdown(label, visible=True):
@@ -1147,16 +1156,16 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
                                         lora5_copy_gui = gr.Button(value="Copy example to prompt", visible=False)
                                     lora5_desc_gui = gr.Markdown(value="", visible=False)
                             with gr.Column():
-                                lora6_gui = lora_dropdown("LoRA6", visible=(not IS_ZERO_GPU))
-                                lora_scale_6_gui = lora_scale_slider("LoRA Scale 6", visible=(not IS_ZERO_GPU))
+                                lora6_gui = lora_dropdown("LoRA6")
+                                lora_scale_6_gui = lora_scale_slider("LoRA Scale 6")
                                 with gr.Row():
                                     with gr.Group():
                                         lora6_info_gui = lora_textbox("LoRA6 prompts")
                                         lora6_copy_gui = gr.Button(value="Copy example to prompt", visible=False)
                                     lora6_desc_gui = gr.Markdown(value="", visible=False)
                             with gr.Column():
-                                lora7_gui = lora_dropdown("LoRA7", visible=(not IS_ZERO_GPU))
-                                lora_scale_7_gui = lora_scale_slider("LoRA Scale 7", visible=(not IS_ZERO_GPU))
+                                lora7_gui = lora_dropdown("LoRA7")
+                                lora_scale_7_gui = lora_scale_slider("LoRA Scale 7")
                                 with gr.Row():
                                     with gr.Group():
                                         lora7_info_gui = lora_textbox("LoRA7 prompts")
@@ -1362,6 +1371,8 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
                         with gr.Accordion("Other settings", open=False, visible=True) as menu_other:
                             with gr.Row():
                                 save_generated_images_gui = gr.Checkbox(value=False, label="Save Generated Images")
+                                enable_live_preview_gui = gr.Checkbox(value=True, label="Enable live previews")
+                                display_images_gui = gr.Checkbox(value=True, label="Show final results")
                                 filename_pattern_gui = gr.Textbox(label="Filename pattern", value="model,seed", placeholder="model,seed,sampler,schedule_type,img_width,img_height,guidance_scale,num_steps,vae,prompt_section,neg_prompt_section", lines=1)
                             with gr.Row():
                                 hires_before_adetailer_gui = gr.Checkbox(value=False, label="Hires Before Adetailer")
@@ -1375,12 +1386,10 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
                         with gr.Accordion("More settings", open=False, visible=False):
                             loop_generation_gui = gr.Slider(minimum=1, value=1, label="Loop Generation")
                             retain_task_cache_gui = gr.Checkbox(value=True, label="Retain task model in cache")
-                            display_images_gui = gr.Checkbox(value=False, label="Display Images")
-                            image_previews_gui = gr.Checkbox(value=True, label="Image Previews")
+                            image_previews_gui = gr.Checkbox(value=True, label="Image Previews (alt)")
                             retain_compel_previous_load_gui = gr.Checkbox(value=False, label="Retain Compel Previous Load")
                             retain_detailfix_model_previous_load_gui = gr.Checkbox(value=False, label="Retain Detailfix Model Previous Load")
                             retain_hires_model_previous_load_gui = gr.Checkbox(value=False, label="Retain Hires Model Previous Load")
-                            xformers_memory_efficient_attention_gui = gr.Checkbox(value=False, label="Xformers Memory Efficient Attention")
 
                         set_params_gui.click(
                             run_set_params_gui, [prompt_gui, model_name_gui], [
@@ -1406,6 +1415,7 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
                                 hires_schedule_type_gui,
                                 image_resolution_gui,
                                 strength_gui,
+                                prompt_syntax_gui,
                                 lora1_gui,
                                 lora_scale_1_gui,
                                 lora2_gui,
@@ -1421,7 +1431,6 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
                                 lora7_gui,
                                 lora_scale_7_gui,
                             ],
-                            show_api=False,
                         )
 
             with gr.Accordion("Examples and help", open=True, visible=True) as menu_example:
@@ -1741,7 +1750,7 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
                 t2i_adapter_preprocessor_gui,
                 adapter_conditioning_scale_gui,
                 adapter_conditioning_factor_gui,
-                xformers_memory_efficient_attention_gui,
+                enable_live_preview_gui,
                 free_u_gui,
                 generator_in_cpu_gui,
                 adetailer_inpaint_only_gui,

constants.py

@@ -16,12 +16,15 @@ IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
 DOWNLOAD_MODEL = "https://huggingface.co/zuv0/test/resolve/main/milkyWonderland_v40.safetensors"
 
 # - **Download VAEs**
-DOWNLOAD_VAE = "https://huggingface.co/fp16-guy/anything_kl-f8-anime2_vae-ft-mse-840000-ema-pruned_blessed_clearvae_fp16_cleaned/resolve/main/vae-ft-mse-840000-ema-pruned_fp16.safetensors?download=true"
+DOWNLOAD_VAE = "https://huggingface.co/Anzhc/Anzhcs-VAEs/resolve/main/SDXL%20Anime%20VAE%20Dec-only%20B3.safetensors, https://huggingface.co/fp16-guy/anything_kl-f8-anime2_vae-ft-mse-840000-ema-pruned_blessed_clearvae_fp16_cleaned/resolve/main/vae-ft-mse-840000-ema-pruned_fp16.safetensors?download=true"
 
 # - **Download LoRAs**
 DOWNLOAD_LORA = "https://huggingface.co/Leopain/color/resolve/main/Coloring_book_-_LineArt.safetensors, https://civitai.com/api/download/models/135867, https://huggingface.co/Linaqruf/anime-detailer-xl-lora/resolve/main/anime-detailer-xl.safetensors?download=true, https://huggingface.co/Linaqruf/style-enhancer-xl-lora/resolve/main/style-enhancer-xl.safetensors?download=true, https://huggingface.co/ByteDance/Hyper-SD/resolve/main/Hyper-SD15-8steps-CFG-lora.safetensors?download=true, https://huggingface.co/ByteDance/Hyper-SD/resolve/main/Hyper-SDXL-8steps-CFG-lora.safetensors?download=true"
 
 LOAD_DIFFUSERS_FORMAT_MODEL = [
+    'TestOrganizationPleaseIgnore/potato_quality_anime_plzwork_sdxl',
+    'TestOrganizationPleaseIgnore/rinAnim8drawIllustriousXL_v20_sdxl',
+    'TestOrganizationPleaseIgnore/perfectrsbmixIllustrious_definitiveiota_sdxl',
     'stabilityai/stable-diffusion-xl-base-1.0',
     'Laxhar/noobai-XL-1.1',
     'Laxhar/noobai-XL-Vpred-1.0',
@@ -51,8 +54,10 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/ntr-mix-illustrious-xl-noob-xl-xi-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xii-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xiii-sdxl',
+    'martineux/nova-unreal10',
     'John6666/mistoon-anime-v10illustrious-sdxl',
     'John6666/hassaku-xl-illustrious-v22-sdxl',
+    'John6666/hassaku-xl-illustrious-v31-sdxl',
     'John6666/haruki-mix-illustrious-v10-sdxl',
     'John6666/noobreal-v10-sdxl',
     'John6666/complicated-noobai-merge-vprediction-sdxl',
@@ -64,6 +69,7 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'Laxhar/noobai-XL-Vpred-0.6',
     'John6666/cat-tower-noobai-xl-checkpoint-v14vpred-sdxl',
     'John6666/cat-tower-noobai-xl-checkpoint-v15vpred-sdxl',
+    'John6666/cat-tower-noobai-xl-checkpoint-v20-vpred-sdxl',
     'John6666/noobai-xl-nai-xl-vpred05version-sdxl',
     'John6666/noobai-fusion2-vpred-itercomp-v1-sdxl',
     'John6666/noobai-xl-nai-xl-vpredtestversion-sdxl',
@@ -78,19 +84,31 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/one-obsession-14-24d-sdxl',
     'John6666/one-obsession-15-noobai-sdxl',
     'John6666/one-obsession-v16-noobai-sdxl',
+    'John6666/one-obsession-17-red-sdxl',
+    'martineux/oneobs18',
+    'martineux/oneobsession19',
+    'John6666/cat-tower-noobai-xl-checkpoint-v14-epsilon-pred-sdxl',
+    'martineux/cattower-chenkin-xl',
     'John6666/prefect-illustrious-xl-v3-sdxl',
+    'martineux/perfect4',
+    'martineux/prefectIllustriousXL_v5',
     'John6666/wai-nsfw-illustrious-v70-sdxl',
     'John6666/wai-nsfw-illustrious-sdxl-v140-sdxl',
+    'martineux/waiIllustriousSDXL_v160',
     'John6666/illustrious-pony-mix-v3-sdxl',
     'John6666/nova-anime-xl-il-v90-sdxl',
     'John6666/nova-anime-xl-il-v110-sdxl',
+    'frankjoshua/novaAnimeXL_ilV140',
     'John6666/nova-orange-xl-re-v10-sdxl',
     'John6666/nova-orange-xl-v110-sdxl',
     'John6666/nova-orange-xl-re-v20-sdxl',
     'John6666/nova-unreal-xl-v60-sdxl',
     'John6666/nova-unreal-xl-v70-sdxl',
     'John6666/nova-unreal-xl-v80-sdxl',
+    'martineux/nova-unreal10',
     'John6666/nova-cartoon-xl-v40-sdxl',
+    'martineux/novacartoon6',
+    'martineux/novareal8',
     'John6666/silvermoon-mix03-illustrious-v10-sdxl',
     'eienmojiki/Anything-XL',
     'eienmojiki/Starry-XL-v5.2',
@@ -151,6 +169,22 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'yodayo-ai/kivotos-xl-2.0',
     'yodayo-ai/holodayo-xl-2.1',
     'yodayo-ai/clandestine-xl-1.0',
+    'Raelina/Raehoshi-illust-XL-8',
+    'johnkillington/chenkinxmilfynoobai_v20-MLX',
+    'martineux/unholydesire5-xl',
+    'abacaxthebrave/Unholy_Desire_Mix_ILXL',
+    'martineux/diving5',
+    'martineux/diving7',
+    'martineux/mergestein-animuplus-xl',
+    'martineux/mergestein-uncannyr2-xl',
+    'martineux/steincustom_V12',
+    'martineux/miaomiao-realskin1p25-xl',
+    'martineux/miaov18',
+    'John6666/garage-mix-noob-vpred-eps-v10-vpred-sdxl',
+    'TestOrganizationPleaseIgnore/perfectrsbmixIllustrious_definitivelambda_sdxl',
+    'TestOrganizationPleaseIgnore/rinFlanimeIllustrious_v27_sdxl',
+    'TestOrganizationPleaseIgnore/rinAnimepopcute_v30_sdxl',
+    'TestOrganizationPleaseIgnore/potato_quality_anime_zzz_sdxl',
     'https://huggingface.co/chemwolf/Karmix-XL-v0/resolve/main/Karmix-XL-v0.safetensors?download=true',
     'https://civitai.com/api/download/models/128713?type=Model&format=SafeTensor&size=pruned&fp=fp16',
     'https://civitai.com/models/30240?modelVersionId=125771',
@@ -603,4 +637,4 @@ RESOURCES = (
     - Try the image generator in Colab’s free tier, which provides free GPU [link](https://github.com/R3gm/SD_diffusers_interactive).
     - `DiffuseCraft` in Colab:[link](https://github.com/R3gm/DiffuseCraft?tab=readme-ov-file#diffusecraft).
     """
-)
+)

modutils.py

@@ -1753,7 +1753,7 @@ EXAMPLES_GUI = [
         "Euler",
         1024,
         1024,
-        "Raelina/Raehoshi-illust-XL-6",
+        "Raelina/Raehoshi-illust-XL-8",
     ],
     [
         "yoshida yuuko, machikado mazoku, 1girl, solo, demon horns,horns, school uniform, long hair, open mouth, skirt, demon girl, ahoge, shiny, shiny hair, anime artwork",

requirements.txt

@@ -1,6 +1,6 @@
 stablepy==0.6.5
 diffusers
-transformers<=4.48.3
+transformers
 accelerate
 huggingface_hub
 hf_transfer