Update dependency diffusers to >=0.39.0,<0.40.0#37
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This PR contains the following updates:
>=0.38.0,<0.39.0→>=0.39.0,<0.40.0Release Notes
huggingface/diffusers (diffusers)
v0.39.0: Diffusers 0.39.0: New image and video pipelines, core library improvements, and moreCompare Source
New Pipelines
Cosmos 3
Cosmos 3 is NVIDIA's unified world foundation model (WFM) for Physical AI — a single omni-model built on a Mixture-of-Transformers (MoT) architecture that combines world generation, physical reasoning, and action generation, replacing the separate Predict, Reason, and Transfer models from earlier Cosmos releases. A single
Cosmos3OmniTransformerruns a Qwen-style language model in parallel with a diffusion generation pathway, joined by a 3D multimodal RoPE. This release also lands video-to-video and action-conditioned generation, and a sound encoder.Thanks to @atharvajoshi10, @yzhautouskay, and @MaciejBalaNV for the contributions.
Ideogram 4
Ideogram 4 is a flow-matching text-to-image model that uses a multimodal text encoder and an asymmetric classifier-free guidance scheme: a dedicated
unconditional_transformerproduces the negative branch with zeroed text features, while the maintransformerconsumes the full packed text + image sequence. The pipeline ships with structured prompt upsampling and LoRA loading support.Thanks to @JinLiIdeogram for the contribution.
Krea 2
Krea 2 (K2) is a flow-matching text-to-image model built around a single-stream MMDiT with grouped-query attention. A Qwen3-VL text encoder provides the conditioning — hidden states from twelve decoder layers are tapped per token and fused inside the transformer by a small text-fusion stage — and images are decoded with the Qwen-Image VAE. Both the base (midtrain) and TDM (distilled, few-step) checkpoints are supported, alongside a LoRA DreamBooth trainer.
Thanks to @EleaZhong and @Abhinay1997 for the contribution.
DreamLite
DreamLite is a text-to-image and image-editing model from ByteDance. It pairs a custom 2D U-Net (
DreamLiteUNetModel) with theQwen3-VLmultimodal encoder as its prompt / image-instruction encoder, and uses anAutoencoderTiny(TAESD-style) VAE for fast latent encode/decode. A distilledDreamLiteMobilePipelinetargets on-device, low-latency generation.Thanks to @Carlofkl for the contribution.
PRX Pixel
PRXPixel is a pixel-space text-to-image generation model by Photoroom. A ~7B
PRXTransformer2DModeldenoises raw RGB images directly — no VAE is needed. The model is conditioned on a Qwen3-VL text encoder and uses flow matching where the transformer predicts the clean image at each step (x-prediction).Thanks to @DavidBert for the contribution.
Motif-Video
Motif-Video is a 2B parameter diffusion transformer for text-to-video and image-to-video generation. It features a three-stage architecture (12 dual-stream + 16 single-stream + 8 DDT decoder layers), Shared Cross-Attention for stable text-video alignment over long sequences, a T5Gemma2 text encoder, and rectified flow matching for velocity prediction.
Thanks to @waitingcheung for the contribution.
AnyFlow
AnyFlow from NVIDIA, NUS, and MIT is the first any-step video diffusion framework built on flow maps, enabling a single model (bidirectional or causal) to adapt to arbitrary inference budgets. It ships both bidirectional and FAR causal pipelines built on Wan2.1 backbones, covering text-to-video, image-to-video, and video-to-video.
Thanks to @Enderfga for the contribution.
JoyAI-Image-Edit
JoyAI-Image is a unified multimodal foundation model for image understanding, text-to-image generation, and instruction-guided image editing. It combines an 8B Multimodal LLM with a 16B Multimodal Diffusion Transformer (MMDiT).
JoyImageEditPipelinesupports general image editing as well as spatial editing capabilities including object move, object rotation, and camera control.Thanks to @Moran232 for the contribution.
DiffusionGemma
DiffusionGemma is a block-diffusion encoder-decoder language model. A causal encoder reads the clean prompt (and any previously generated blocks) into a KV cache, and a bidirectional decoder denoises a fixed-size "canvas" of tokens by cross-attending to that cache, committing the most confident tokens via the new
BlockRefinementScheduler. The released checkpoint isgoogle/diffusiongemma-26B-A4B-it.Anima
Anima is a 2 billion parameter text-to-image model created via a collaboration between CircleStone Labs and Comfy Org. It is focused mainly on anime concepts, characters, and styles, but is also capable of generating a wide variety of other non-photorealistic content.
It reuses the CosmosTransformer3DModel with a Qwen3 text encoder, a T5-token text conditioner, and the AutoencoderKLQwenImage VAE.
Thanks to @rmatif for the contribution.
LTX-2.X IC LoRA and HDR Pipelines
New
LTX2InContextPipeline(in-context LoRA) andLTX2HDRPipelineextend the LTX-2 family with in-context conditioning and HDR video generation.Modular Pipeline Support
ErnieImageModularPipeline(#13948) andIdeogram4ModularPipeline(#13980), thanks to @SamuelTallet.Core Library
_dequantizefor the TorchAO quantizerAutoPipelineForText2Audiotorch.compilecompatibilitysafetensorsto 0.8.0torchversion is now 2.6All commits
txt_seq_lensfrom qwen transformer. by @sayakpaul in #13674torch.distributedby @hlky in #13673flash_varlen_hubbackend by @zhtmike in #13479transformersfrom main for doc and staging by @sayakpaul in #13723modules_to_not_convert/keep_in_fp32_modulesby @dg845 in #13697weightingchunk when using prior preservation in Flux and SD3 LoRA training by @Dev-X25874 in #13743torch_deviceimport in AutoencoderTesterMixin by @DN6 in #13852device_map="auto"in single file tests to support large models on limited GPU memory by @jiqing-feng in #13816cond_model_inputin Flux2 Klein img2img training by @HaozheZhang6 in #13923ErnieImageModularPipelineby @SamuelTallet in #13948AutoModelby @neo in #13889Ideogram4ModularPipelineby @SamuelTallet in #13980torch.compilecompatibility with Neuron device by @JingyaHuang in #13485Ideogram4MRoPEcollapsing undertorch.autocast(compute rotary in float32) by @HaozheZhang6 in #13922Significant community contributions
The following contributors have made significant changes to the library over the last release:
torch_deviceimport in AutoencoderTesterMixin (#13852)modules_to_not_convert/keep_in_fp32_modules(#13697)Configuration
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