let's go Flux2 🚀 (#12711)

* add vae

* Initial commit for Flux 2 Transformer implementation

* add pipeline part

* small edits to the pipeline and conversion

* update conversion script

* fix

* up up

* finish pipeline

* Remove Flux IP Adapter logic for now

* Remove deprecated 3D id logic

* Remove ControlNet logic for now

* Add link to ViT-22B paper as reference for parallel transformer blocks such as the Flux 2 single stream block

* update pipeline

* Don't use biases for input projs and output AdaNorm

* up

* Remove bias for double stream block text QKV projections

* Add script to convert Flux 2 transformer to diffusers

* make style and make quality

* fix a few things.

* allow sft files to go.

* fix image processor

* fix batch

* style a bit

* Fix some bugs in Flux 2 transformer implementation

* Fix dummy input preparation and fix some test bugs

* fix dtype casting in timestep guidance module.

* resolve conflicts.,

* remove ip adapter stuff.

* Fix Flux 2 transformer consistency test

* Fix bug in Flux2TransformerBlock (double stream block)

* Get remaining Flux 2 transformer tests passing

* make style; make quality; make fix-copies

* remove stuff.

* fix type annotaton.

* remove unneeded stuff from tests

* tests

* up

* up

* add sf support

* Remove unused IP Adapter and ControlNet logic from transformer (#9)

* copied from

* Apply suggestions from code review

Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: apolinário <joaopaulo.passos@gmail.com>

* up

* up

* up

* up

* up

* Refactor Flux2Attention into separate classes for double stream and single stream attention

* Add _supports_qkv_fusion to AttentionModuleMixin to allow subclasses to disable QKV fusion

* Have Flux2ParallelSelfAttention inherit from AttentionModuleMixin with _supports_qkv_fusion=False

* Log debug message when calling fuse_projections on a AttentionModuleMixin subclass that does not support QKV fusion

* Address review comments

* Update src/diffusers/pipelines/flux2/pipeline_flux2.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* up

* Remove maybe_allow_in_graph decorators for Flux 2 transformer blocks (#12)

* up

* support ostris loras. (#13)

* up

* update schdule

* up

* up (#17)

* add training scripts (#16)

* add training scripts

Co-authored-by: Linoy Tsaban <linoytsaban@gmail.com>

* model cpu offload in validation.

* add flux.2 readme

* add img2img and tests

* cpu offload in log validation

* Apply suggestions from code review

* fix

* up

* fixes

* remove i2i training tests for now.

---------

Co-authored-by: Linoy Tsaban <linoytsaban@gmail.com>
Co-authored-by: linoytsaban <linoy@huggingface.co>

* up

---------

Co-authored-by: yiyixuxu <yixu310@gmail.com>
Co-authored-by: Daniel Gu <dgu8957@gmail.com>
Co-authored-by: yiyi@huggingface.co <yiyi@ip-10-53-87-203.ec2.internal>
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: apolinário <joaopaulo.passos@gmail.com>
Co-authored-by: yiyi@huggingface.co <yiyi@ip-26-0-160-103.ec2.internal>
Co-authored-by: Linoy Tsaban <linoytsaban@gmail.com>
Co-authored-by: linoytsaban <linoy@huggingface.co>

docs/source/en/_toctree.yml

@@ -349,6 +349,8 @@
         title: DiTTransformer2DModel
       - local: api/models/easyanimate_transformer3d
         title: EasyAnimateTransformer3DModel
+      - local: api/models/flux2_transformer
+        title: Flux2Transformer2DModel
       - local: api/models/flux_transformer
         title: FluxTransformer2DModel
       - local: api/models/hidream_image_transformer
@@ -525,6 +527,8 @@
         title: EasyAnimate
       - local: api/pipelines/flux
         title: Flux
+      - local: api/pipelines/flux2
+        title: Flux2
       - local: api/pipelines/control_flux_inpaint
         title: FluxControlInpaint
       - local: api/pipelines/hidream

docs/source/en/api/loaders/lora.md

@@ -30,7 +30,8 @@ LoRA is a fast and lightweight training method that inserts and trains a signifi
 - [`CogView4LoraLoaderMixin`] provides similar functions for [CogView4](https://huggingface.co/docs/diffusers/main/en/api/pipelines/cogview4).
 - [`AmusedLoraLoaderMixin`] is for the [`AmusedPipeline`].
 - [`HiDreamImageLoraLoaderMixin`] provides similar functions for [HiDream Image](https://huggingface.co/docs/diffusers/main/en/api/pipelines/hidream)
-- [`QwenImageLoraLoaderMixin`] provides similar functions for [Qwen Image](https://huggingface.co/docs/diffusers/main/en/api/pipelines/qwen)
+- [`QwenImageLoraLoaderMixin`] provides similar functions for [Qwen Image](https://huggingface.co/docs/diffusers/main/en/api/pipelines/qwen).
+- [`Flux2LoraLoaderMixin`] provides similar functions for [Flux2](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux2).
 - [`LoraBaseMixin`] provides a base class with several utility methods to fuse, unfuse, unload, LoRAs and more.
 
 > [!TIP]
@@ -56,6 +57,10 @@ LoRA is a fast and lightweight training method that inserts and trains a signifi
 
 [[autodoc]] loaders.lora_pipeline.FluxLoraLoaderMixin
 
+## Flux2LoraLoaderMixin
+
+[[autodoc]] loaders.lora_pipeline.Flux2LoraLoaderMixin
+
 ## CogVideoXLoraLoaderMixin
 
 [[autodoc]] loaders.lora_pipeline.CogVideoXLoraLoaderMixin

docs/source/en/api/models/flux2_transformer.md

@@ -0,0 +1,19 @@
+<!--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.
+-->
+
+# Flux2Transformer2DModel
+
+A Transformer model for image-like data from [Flux2](https://hf.co/black-forest-labs/FLUX.2-dev).
+
+## Flux2Transformer2DModel
+
+[[autodoc]] Flux2Transformer2DModel

docs/source/en/api/pipelines/flux2.md

@@ -0,0 +1,33 @@
+<!--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.
+-->
+
+# Flux2
+
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+  <img alt="MPS" src="https://img.shields.io/badge/MPS-000000?style=flat&logo=apple&logoColor=white%22">
+</div>
+
+Flux.2 is the recent series of image generation models from Black Forest Labs, preceded by the [Flux.1](./flux.md) series. It is an entirely new model with a new architecture and pre-training done from scratch!
+
+Original model checkpoints for Flux can be found [here](https://huggingface.co/black-forest-labs). Original inference code can be found [here](https://github.com/black-forest-labs/flux2-dev).
+
+> [!TIP]
+> Flux2 can be quite expensive to run on consumer hardware devices. However, you can perform a suite of optimizations to run it faster and in a more memory-friendly manner. Check out [this section](https://huggingface.co/blog/sd3#memory-optimizations-for-sd3) for more details. Additionally, Flux can benefit from quantization for memory efficiency with a trade-off in inference latency. Refer to [this blog post](https://huggingface.co/blog/quanto-diffusers) to learn more.
+>
+> [Caching](../../optimization/cache) may also speed up inference by storing and reusing intermediate outputs.
+
+## Flux2Pipeline
+
+[[autodoc]] Flux2Pipeline
+	- all
+	- __call__