Add STORK scheduler

docs/source/en/_toctree.yml

@@ -30,7 +30,8 @@
   - local: using-diffusers/push_to_hub
     title: Push files to the Hub
   title: Load pipelines and adapters
-- sections:
+- isExpanded: false
+  sections:
   - local: tutorials/using_peft_for_inference
     title: LoRA
   - local: using-diffusers/ip_adapter
@@ -44,7 +45,6 @@
   - local: using-diffusers/textual_inversion_inference
     title: Textual inversion
   title: Adapters
-  isExpanded: false
 - sections:
   - local: using-diffusers/unconditional_image_generation
     title: Unconditional image generation
@@ -652,6 +652,8 @@
       title: ScoreSdeVeScheduler
     - local: api/schedulers/score_sde_vp
       title: ScoreSdeVpScheduler
+    - local: api/schedulers/stork
+      title: STORKScheduler
     - local: api/schedulers/tcd
       title: TCDScheduler
     - local: api/schedulers/unipc

docs/source/en/api/schedulers/stork.md

@@ -0,0 +1,23 @@
+<!--Copyright 2025 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+-->
+
+# STORKScheduler
+`STORKScheduler` is the sampling method from the paper [STORK: Improving the Fidelity of Mid-NFE Sampling for Diffusion and Flow Matching Models](https://arxiv.org/abs/2505.24210) by [Zheng Tan](https://zt220501.github.io/), [Weizhen Wang](https://weizhenwang-1210.github.io/), [Andrea L. Bertozzi](https://www.math.ucla.edu/~bertozzi/), and [Ernest K. Ryu](https://ernestryu.com/). It was motivated by stabilized Runge--Kutta methods, with Taylor expansion adaptation for diffusion and flow matching models.
+
+--------------------
+
+## STORKScheduler
+[[autodoc]] STORKScheduler
+
+## SchedulerOutput
+[[autodoc]] schedulers.scheduling_utils.SchedulerOutput
+

src/diffusers/__init__.py

@@ -286,6 +286,7 @@
             "SchedulerMixin",
             "SCMScheduler",
             "ScoreSdeVeScheduler",
+            "STORKScheduler",
             "TCDScheduler",
             "UnCLIPScheduler",
             "UniPCMultistepScheduler",

src/diffusers/schedulers/__init__.py

@@ -71,6 +71,7 @@
     _import_structure["scheduling_sasolver"] = ["SASolverScheduler"]
     _import_structure["scheduling_scm"] = ["SCMScheduler"]
     _import_structure["scheduling_sde_ve"] = ["ScoreSdeVeScheduler"]
+    _import_structure["scheduling_stork"] = ["STORKScheduler"]
     _import_structure["scheduling_tcd"] = ["TCDScheduler"]
     _import_structure["scheduling_unclip"] = ["UnCLIPScheduler"]
     _import_structure["scheduling_unipc_multistep"] = ["UniPCMultistepScheduler"]
@@ -173,6 +174,7 @@
         from .scheduling_sasolver import SASolverScheduler
         from .scheduling_scm import SCMScheduler
         from .scheduling_sde_ve import ScoreSdeVeScheduler
+        from .scheduling_stork import STORKScheduler
         from .scheduling_tcd import TCDScheduler
         from .scheduling_unclip import UnCLIPScheduler
         from .scheduling_unipc_multistep import UniPCMultistepScheduler