Bria 3 2 pipeline

docs/source/en/_toctree.yml

@@ -326,6 +326,8 @@
         title: AllegroTransformer3DModel
       - local: api/models/aura_flow_transformer2d
         title: AuraFlowTransformer2DModel
+      - local: api/models/bria_transformer2d
+        title: BriaTransformer2DModel
       - local: api/models/chroma_transformer
         title: ChromaTransformer2DModel
       - local: api/models/cogvideox_transformer3d
@@ -454,6 +456,8 @@
       title: AutoPipeline
     - local: api/pipelines/blip_diffusion
       title: BLIP-Diffusion
+    - local: api/pipelines/bria_3_2
+      title: Bria 3.2
     - local: api/pipelines/chroma
       title: Chroma
     - local: api/pipelines/cogvideox

docs/source/en/api/models/bria_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.
+-->
+
+# BriaTransformer2DModel
+
+A modified flux Transformer model from [Bria](https://huggingface.co/briaai/BRIA-3.2)
+
+## BriaTransformer2DModel
+
+[[autodoc]] BriaTransformer2DModel

docs/source/en/api/pipelines/bria_3_2.md

@@ -0,0 +1,60 @@
+<!--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.
+-->
+
+# Bria 3.2
+
+Bria 3.2 is the next-generation commercial-ready text-to-image model. With just 4 billion parameters, it provides exceptional aesthetics and text rendering, evaluated to provide on par results to leading open-source models, and outperforming other licensed models.
+In addition to being built entirely on licensed data, 3.2 provides several advantages for enterprise and commercial use:
+
+- Efficient Compute - the model is X3 smaller than the equivalent models in the market (4B parameters vs 12B parameters other open source models)
+- Architecture Consistency: Same architecture as 3.1—ideal for users looking to upgrade without disruption.
+- Fine-tuning Speedup: 2x faster fine-tuning on L40S and A100.
+
+Original model checkpoints for Bria 3.2 can be found [here](https://huggingface.co/briaai/BRIA-3.2).
+Github repo for Bria 3.2 can be found [here](https://github.com/Bria-AI/BRIA-3.2).
+
+If you want to learn more about the Bria platform, and get free traril access, please visit [bria.ai](https://bria.ai).
+
+
+## Usage
+
+_As the model is gated, before using it with diffusers you first need to go to the [Bria 3.2 Hugging Face page](https://huggingface.co/briaai/BRIA-3.2), fill in the form and accept the gate. Once you are in, you need to login so that your system knows you’ve accepted the gate._
+
+Use the command below to log in:
+
+```bash
+hf auth login
+```
+
+## Inference
+
+
+```python
+import torch
+from diffusers import BriaPipeline
+
+pipe = BriaPipeline.from_pretrained("briaai/BRIA-3.2",revision="bria_3_2_diffusers", torch_dtype=torch.bfloat16)
+pipe.enable_model_cpu_offload()
+
+prompt = "A high-fashion close-up portrait of a blonde woman in clear sunglasses. The image uses a bold teal and red color split for dramatic lighting. The background is a simple teal-green. The photo is sharp and well-composed, and is designed for viewing with anaglyph 3D glasses for optimal effect. It looks professionally done."
+
+image = pipe(prompt).images[0]
+image.save("bria.png")
+```
+
+
+## BriaPipeline
+
+[[autodoc]] BriaPipeline
+	- all
+	- __call__
+

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

@@ -37,6 +37,7 @@ The table below lists all the pipelines currently available in 🤗 Diffusers an
 | [AudioLDM2](audioldm2) | text2audio |
 | [AuraFlow](auraflow) | text2image |
 | [BLIP Diffusion](blip_diffusion) | text2image |
+| [Bria 3.2](bria_3_2) | text2image |
 | [CogVideoX](cogvideox) | text2video |
 | [Consistency Models](consistency_models) | unconditional image generation |
 | [ControlNet](controlnet) | text2image, image2image, inpainting |

src/diffusers/__init__.py

@@ -181,6 +181,7 @@
             "AutoencoderOobleck",
             "AutoencoderTiny",
             "AutoModel",
+            "BriaTransformer2DModel",
             "CacheMixin",
             "ChromaTransformer2DModel",
             "CogVideoXTransformer3DModel",
@@ -397,6 +398,7 @@
             "AuraFlowPipeline",
             "BlipDiffusionControlNetPipeline",
             "BlipDiffusionPipeline",
+            "BriaPipeline",
             "ChromaImg2ImgPipeline",
             "ChromaPipeline",
             "CLIPImageProjection",
@@ -843,6 +845,7 @@
             AutoencoderOobleck,
             AutoencoderTiny,
             AutoModel,
+            BriaTransformer2DModel,
             CacheMixin,
             ChromaTransformer2DModel,
             CogVideoXTransformer3DModel,
@@ -1034,6 +1037,7 @@
             AudioLDM2UNet2DConditionModel,
             AudioLDMPipeline,
             AuraFlowPipeline,
+            BriaPipeline,
             ChromaImg2ImgPipeline,
             ChromaPipeline,
             CLIPImageProjection,

src/diffusers/hooks/_helpers.py

@@ -144,6 +144,7 @@ def _register_attention_processors_metadata():
 def _register_transformer_blocks_metadata():
     from ..models.attention import BasicTransformerBlock
     from ..models.transformers.cogvideox_transformer_3d import CogVideoXBlock
+    from ..models.transformers.transformer_bria import BriaTransformerBlock
     from ..models.transformers.transformer_cogview4 import CogView4TransformerBlock
     from ..models.transformers.transformer_flux import FluxSingleTransformerBlock, FluxTransformerBlock
     from ..models.transformers.transformer_hunyuan_video import (
@@ -165,6 +166,13 @@ def _register_transformer_blocks_metadata():
             return_encoder_hidden_states_index=None,
         ),
     )
+    TransformerBlockRegistry.register(
+        model_class=BriaTransformerBlock,
+        metadata=TransformerBlockMetadata(
+            return_hidden_states_index=0,
+            return_encoder_hidden_states_index=None,
+        ),
+    )
 
     # CogVideoX
     TransformerBlockRegistry.register(

src/diffusers/models/__init__.py

@@ -76,6 +76,7 @@
     _import_structure["transformers.t5_film_transformer"] = ["T5FilmDecoder"]
     _import_structure["transformers.transformer_2d"] = ["Transformer2DModel"]
     _import_structure["transformers.transformer_allegro"] = ["AllegroTransformer3DModel"]
+    _import_structure["transformers.transformer_bria"] = ["BriaTransformer2DModel"]
     _import_structure["transformers.transformer_chroma"] = ["ChromaTransformer2DModel"]
     _import_structure["transformers.transformer_cogview3plus"] = ["CogView3PlusTransformer2DModel"]
     _import_structure["transformers.transformer_cogview4"] = ["CogView4Transformer2DModel"]
@@ -158,6 +159,7 @@
         from .transformers import (
             AllegroTransformer3DModel,
             AuraFlowTransformer2DModel,
+            BriaTransformer2DModel,
             ChromaTransformer2DModel,
             CogVideoXTransformer3DModel,
             CogView3PlusTransformer2DModel,

src/diffusers/models/embeddings.py

@@ -1220,7 +1220,6 @@ def apply_rotary_emb(
             x_rotated = torch.cat([-x_imag, x_real], dim=-1)
         else:
             raise ValueError(f"`use_real_unbind_dim={use_real_unbind_dim}` but should be -1 or -2.")
-
         out = (x.float() * cos + x_rotated.float() * sin).to(x.dtype)
 
         return out

src/diffusers/models/transformers/__init__.py

@@ -17,6 +17,7 @@
     from .t5_film_transformer import T5FilmDecoder
     from .transformer_2d import Transformer2DModel
     from .transformer_allegro import AllegroTransformer3DModel
+    from .transformer_bria import BriaTransformer2DModel
     from .transformer_chroma import ChromaTransformer2DModel
     from .transformer_cogview3plus import CogView3PlusTransformer2DModel
     from .transformer_cogview4 import CogView4Transformer2DModel