diff --git a/modules/processing_diffusers.py b/modules/processing_diffusers.py
index ca4782576..2fa1d814d 100644
--- a/modules/processing_diffusers.py
+++ b/modules/processing_diffusers.py
@@ -182,6 +182,13 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
                 shared.log.error(f'Prompt parser encode: {e}')
                 if os.environ.get('SD_PROMPT_DEBUG', None) is not None:
                     errors.display(e, 'Prompt parser encode')
+        if parser == 'Fixed attention':
+            clip_skip = kwargs.pop("clip_skip", None)
+            if clip_skip is not None:
+                if 'XL' in model.__class__.__name__:
+                    args['clip_skip'] = clip_skip - 2
+                else:
+                    args['clip_skip'] = clip_skip - 1
         if 'prompt' in possible:
             if hasattr(model, 'text_encoder') and 'prompt_embeds' in possible and len(p.prompt_embeds) > 0 and p.prompt_embeds[0] is not None:
                 args['prompt_embeds'] = p.prompt_embeds[0]
@@ -410,7 +417,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
         denoising_start=0 if use_refiner_start else p.refiner_start if use_denoise_start else None,
         denoising_end=p.refiner_start if use_refiner_start else 1 if use_denoise_start else None,
         output_type='latent' if hasattr(shared.sd_model, 'vae') else 'np',
-        clip_skip=p.clip_skip - 1,
+        clip_skip=p.clip_skip,
         desc='Base',
     )
     update_sampler(shared.sd_model)
@@ -487,7 +494,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
                     guidance_scale=p.image_cfg_scale if p.image_cfg_scale is not None else p.cfg_scale,
                     guidance_rescale=p.diffusers_guidance_rescale,
                     output_type='latent' if hasattr(shared.sd_model, 'vae') else 'np',
-                    clip_skip=p.clip_skip - 1,
+                    clip_skip=p.clip_skip,
                     image=output.images,
                     strength=p.denoising_strength,
                     desc='Hires',
@@ -546,7 +553,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
                 denoising_end=1 if p.refiner_start > 0 and p.refiner_start < 1 else None,
                 image=image,
                 output_type=output_type,
-                clip_skip=p.clip_skip - 1,
+                clip_skip=p.clip_skip,
                 desc='Refiner',
             )
             shared.state.sampling_steps = refiner_args['num_inference_steps']