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* Add Bria model and pipeline to diffusers - Introduced `BriaTransformer2DModel` and `BriaPipeline` for enhanced image generation capabilities. - Updated import structures across various modules to include the new Bria components. - Added utility functions and output classes specific to the Bria pipeline. - Implemented tests for the Bria pipeline to ensure functionality and output integrity. * with working tests * style and quality pass * adding docs * add to overview * fixes from "make fix-copies" * Refactor transformer_bria.py and pipeline_bria.py: Introduce new EmbedND class for rotary position embedding, and enhance Timestep and TimestepProjEmbeddings classes. Add utility functions for handling negative prompts and generating original sigmas in pipeline_bria.py. * remove redundent and duplicates tests and fix bf16 slow test * style fixes * small doc update * Enhance Bria 3.2 documentation and implementation - Updated the GitHub repository link for Bria 3.2. - Added usage instructions for the gated model access. - Introduced the BriaTransformerBlock and BriaAttention classes to the model architecture. - Refactored existing classes to integrate Bria-specific components, including BriaEmbedND and BriaPipeline. - Updated the pipeline output class to reflect Bria-specific functionality. - Adjusted test cases to align with the new Bria model structure. * Refactor Bria model components and update documentation - Removed outdated inference example from Bria 3.2 documentation. - Introduced the BriaTransformerBlock class to enhance model architecture. - Updated attention handling to use `attention_kwargs` instead of `joint_attention_kwargs`. - Improved import structure in the Bria pipeline to handle optional dependencies. - Adjusted test cases to reflect changes in model dtype assertions. * Update Bria model reference in documentation to reflect new file naming convention * Update docs/source/en/_toctree.yml * Refactor BriaPipeline to inherit from DiffusionPipeline instead of FluxPipeline, updating imports accordingly. * move the __call__ func to the end of file * Update BriaPipeline example to use bfloat16 for precision sensitivity for better result * make style && make quality && make fix-copiessource --------- Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com> Co-authored-by: Aryan <contact.aryanvs@gmail.com>
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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. Github repo for Bria 3.2 can be found here.
If you want to learn more about the Bria platform, and get free traril access, please visit 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, 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:
hf auth login
BriaPipeline
autodoc BriaPipeline - all - call