ernie enable/disable built-in pe

Signed-off-by: vladmandic <mandic00@live.com>

CHANGELOG.md

@@ -22,6 +22,7 @@ In addition, to jump on a bandwagon, we're now fully **AI agent** ready with det
     *note*: requires large number of steps to achieve sane results  
   - [Baidu ERNIE-Image](https://huggingface.co/baidu/ERNIE-Image) in *base* and *turbo* (distilled) variants  
     ERNIE is single-stream 8B DiT model with built-in prompt enhancer using Mistral-3 text encoder  
+    *note*: ERNIE has a built-in prompt-enhancer which is disabled by default, can be enabled in *settings -> model options*  
   - [Nucleus-Image](https://huggingface.co/NucleusAI/Nucleus-Image)  
     Nucleus is MoE text-to-image model with 2B active and 17B total params
   - [Bria FIBO](https://huggingface.co/briaai/FIBO) in *Normal*, *Edit*, and *Lite* (distilled) variants  

modules/ui_definitions.py

@@ -110,6 +110,8 @@ def create_settings(cmd_opts):
         "model_chrono_temporal_steps": OptionInfo(0, "Temporal steps", gr.Slider, {"minimum": 0, "maximum": 50, "step": 1 }),
         "model_qwen_layer_sep": OptionInfo("<h2>Qwen layered</h2>", "", gr.HTML),
         "model_qwen_layers": OptionInfo(2, "Qwen layered number of layers", gr.Slider, {"minimum": 2, "maximum": 9, "step": 1 }),
+        "model_ernie_sep": OptionInfo("<h2>ERNIE-Image</h2>", "", gr.HTML),
+        "model_ernie_enable_pe": OptionInfo(False, "Enable prompt-enhance"),
     }))
 
     # --- Model Offloading ---

pipelines/model_ernie.py

@@ -12,7 +12,7 @@ def load_ernie_image(checkpoint_info, diffusers_load_config=None):
     sd_models.hf_auth_check(checkpoint_info)
 
     load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, allow_quant=False)
-    log.debug(f'Load model: type=ERNIE-Image repo="{repo_id}" offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
+    log.debug(f'Load model: type=ERNIE-Image repo="{repo_id}" offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args} pe={shared.opts.model_ernie_enable_pe}')
 
     transformer = generic.load_transformer(
         repo_id,
@@ -25,6 +25,9 @@ def load_ernie_image(checkpoint_info, diffusers_load_config=None):
         load_config=diffusers_load_config,
     )
 
+    if not shared.opts.model_ernie_enable_pe:
+        load_args['pe'] = False
+
     pipe = diffusers.ErnieImagePipeline.from_pretrained(
         repo_id,
         cache_dir=shared.opts.diffusers_dir,
@@ -34,6 +37,7 @@ def load_ernie_image(checkpoint_info, diffusers_load_config=None):
     )
     pipe.task_args = {
         'output_type': 'np',
+        'use_pe': shared.opts.model_ernie_enable_pe,
     }
 
     del transformer