[
  {
    "additions": 25,
    "author": "sywangyi",
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    "body_excerpt": "following case fail tests/models/transformers/test_models_transformer_bria.py::BriaTransformerLoRAHotSwapTests::test_hotswapping_compiled_model_linear_2 tests/models/transformers/test_models_transformer_bria.py::BriaTransformerLoRAHotSwapT\u2026",
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    "title": "fix the test_hotswapping_compiled_model_xxx case failure in xpu",
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  },
  {
    "additions": 1,
    "author": "kaixuanliu",
    "author_association": "CONTRIBUTOR",
    "body_excerpt": "This PR tries to fix 2 failed test cases for hiream pipeline tests: ``` tests/pipelines/hidream_image/test_pipeline_hidream.py::HiDreamImagePipelineFastTests::test_cpu_offload_forward_pass_twice tests/pipelines/hidream_image/test_pipeline_\u2026",
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    "title": "Fix non-deterministic T5 outputs in HiDream pipeline tests",
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  },
  {
    "additions": 2,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## What does this PR do? Both `AuraFlowAttnProcessor2_0` and `FusedAuraFlowAttnProcessor2_0` in `attention_processor.py` contain a copy-paste error where `attn.norm_added_q` is called on the encoder **key** projection while guarded by a ch\u2026",
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    "number": 13533,
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    "title": "Fix AuraFlow attn processors applying norm_added_q to key projection",
    "updated_at": "2026-04-21T19:20:55Z"
  },
  {
    "additions": 2,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## What this PR does When a user passes pre-computed `prompt_embeds` (or `negative_prompt_embeds`) alongside `num_images_per_prompt > 1`, `ErnieImagePipeline.__call__` did not replicate the provided embeddings \u2014 the embeds list kept its or\u2026",
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    "title": "Fix ErnieImagePipeline pre-computed prompt_embeds + num_images_per_prompt shape mismatch",
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  },
  {
    "additions": 0,
    "author": "Ricardo-M-L",
    "author_association": "FIRST_TIME_CONTRIBUTOR",
    "body_excerpt": "## What this PR does `train_sana_sprint_diffusers.py` ends training (under `--push_to_hub`) with: https://github.com/huggingface/diffusers/blob/main/examples/research_projects/sana/train_sana_sprint_diffusers.py#L1758-L1766 ```python if ar\u2026",
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    "title": "Fix AttributeError/TypeError in sana_sprint model-card save",
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  },
  {
    "additions": 64,
    "author": "jiqing-feng",
    "author_association": "CONTRIBUTOR",
    "body_excerpt": "## What does this PR do? This PR improves the TorchAO quantization testing infrastructure with several fixes: enabling `int4wo` tests on Intel XPU, implementing `_dequantize` for TorchAO, fixing input dtype mismatches, and fixing training\u2026",
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    "title": "Improve TorchAO quantization test coverage and XPU support",
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  },
  {
    "additions": 4,
    "author": "Ricardo-M-L",
    "author_association": "FIRST_TIME_CONTRIBUTOR",
    "body_excerpt": "## What this PR does Both Wuerstchen prior training scripts build their HF Hub model card with an f-string that references `{args.weight_dtype}`: **`train_text_to_image_prior.py`** (lines 104-105): ```python pipe_prior = DiffusionPipeline.\u2026",
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    "title": "Fix AttributeError in Wuerstchen prior training model card",
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  },
  {
    "additions": 9,
    "author": "Ricardo-M-L",
    "author_association": "FIRST_TIME_CONTRIBUTOR",
    "body_excerpt": "## What this PR does The Intel/BF16 `textual_inversion_bf16.py` script reads `args.report_to` at the top of `main()`: https://github.com/huggingface/diffusers/blob/main/examples/research_projects/intel_opts/textual_inversion/textual_invers\u2026",
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    "title": "Fix AttributeError in textual_inversion_bf16 by adding --report_to arg",
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  },
  {
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    "author": "Ricardo-M-L",
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    "body_excerpt": "## What this PR does `ZImageOmniPipeline.__call__` defines `negative_condition_siglip_embeds` only inside the CFG guard: https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/z_image/pipeline_z_image_omni.py#L581-L582\u2026",
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    "state": "open",
    "title": "Fix NameError in ZImageOmniPipeline when guidance_scale=0",
    "updated_at": "2026-04-21T20:16:08Z"
  },
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    "additions": 1,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## What this PR does `LongCatImageEditPipeline._encode_prompt` calls `len()` twice on an `int` when building its truncation warning message: https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/longcat_image/pipeline_\u2026",
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    "title": "Fix TypeError in LongCatImageEditPipeline truncation warning",
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  },
  {
    "additions": 4,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## What this PR does In `LongCatAudioDiTPipeline.__call__`, positive prompts are normalized via `_normalize_text` before being encoded: ```python normalized_prompts = [_normalize_text(text) for text in prompt] ... prompt_embeds, prompt_emb\u2026",
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  {
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    "author": "Ricardo-M-L",
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    "body_excerpt": "## What does this PR do? The ORT variant of the unconditional training script, `examples/research_projects/onnxruntime/unconditional_image_generation/train_unconditional.py`, defines the tracker flag as `--logger` on the parser: ```python\u2026",
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    "title": "Fix AttributeError in onnxruntime train_unconditional (args.report_to \u2192 args.logger)",
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    "additions": 1,
    "author": "Ricardo-M-L",
    "author_association": "FIRST_TIME_CONTRIBUTOR",
    "body_excerpt": "## What does this PR do? `extract_glyph_texts` in the HunyuanVideo 1.5 modular pipeline had a copy-paste typo in its regex: ```python # src/diffusers/modular_pipelines/hunyuan_video1_5/encoders.py pattern = r\"\\\"(.*?)\\\"|\\\"(.*?)\\\"\" ``` Both\u2026",
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    "title": "Fix HunyuanVideo 1.5 modular glyph regex for curly quotes",
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    "body_excerpt": "## What does this PR do? Fixes an `AttributeError` in `examples/research_projects/diffusion_dpo/train_diffusion_dpo.py` that crashes the IPO loss path. The IPO branch references `args.beta`: ```python elif args.loss_type == \"ipo\": losses =\u2026",
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    "body_excerpt": "## What does this PR do? Fixes a latent `AttributeError` in `examples/t2i_adapter/train_t2i_adapter_sdxl.py` that breaks `--resume_from_checkpoint`. The accelerate `load_model_hook` references `args.control_type`, which is never declared a\u2026",
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    "body_excerpt": "## What does this PR do? Fixes an `AttributeError` in `examples/dreambooth/train_dreambooth_lora_flux2_img2img.py` that makes the validation flow unusable. The validation block references `args.validation_image_path`: ```python if args.val\u2026",
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    "body_excerpt": "## What does this PR do? `FluxControlNetImg2ImgPipeline` and `FluxControlNetInpaintPipeline` already pre-resize `control_image` to `batch_size * num_images_per_prompt`, but only reshape `control_mode` to `[1, 1]`: ```python if control_mode\u2026",
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    "title": "Fix FluxControlNet img2img/inpainting with num_images_per_prompt>1",
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    "body_excerpt": "## What does this PR do? Fixes #13062. \\`diffusers.utils.import_utils\\` probes for onnxruntime by first calling \\`find_spec(\\\"onnxruntime\\\")\\` and then iterating a list of package names to resolve the installed version via \\`importlib_meta\u2026",
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    "body_excerpt": "## What does this PR do? Fixes #12540. When \\`SanaTransformer2DModel\\` is built with \\`guidance_embeds=True\\` and then driven by a pipeline that does not thread \\`guidance\\` through (\\`SanaPipeline\\`, \\`SanaPAGPipeline\\`), the transformer\u2026",
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    "body_excerpt": "## What does this PR do? `CosineDPMSolverMultistepScheduler.step` constructs `BrownianTreeNoiseSampler` with the **config** bounds: ```python self.noise_sampler = BrownianTreeNoiseSampler( model_output, sigma_min=self.config.sigma_min, sig\u2026",
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    "body_excerpt": "## What does this PR do? `gather_size_by_comm` in `src/diffusers/models/_modeling_parallel.py` unconditionally calls `torch.accelerator.current_accelerator()` whenever the backend isn't CPU: ```python gather_device = \"cpu\" if \"cpu\" in comm\u2026",
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    "body_excerpt": "## What does this PR do? Fixes #12913. \\`Lumina2Pipeline.__call__\\` passes \\`latents.shape[1]\\` as \\`image_seq_len\\` when computing \\`mu\\` for the flow-match scheduler: \\`\\`\\`python image_seq_len = latents.shape[1] mu = calculate_shift( im\u2026",
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    "body_excerpt": "# What does this PR do? support AutoPipelineForText2Audio for ext2Audio model ``` import torch import soundfile as sf from diffusers import AutoPipelineForText2Audio pipeline = AutoPipelineForText2Audio.from_pretrained( \"stabilityai/stable\u2026",
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    "body_excerpt": "## What does this PR do? Fixes a regression that aborts \\`examples/dreambooth/train_dreambooth_lora.py\\` on the first training step **after** the first validation, whenever the user combines \\`--mixed_precision=fp16\\` and \\`--validation_pr\u2026",
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    "body_excerpt": "## What does this PR do? Fixes a latent bug in `randn_tensor` where the MPS-specific info-log suppression has been broken since PR #1902 (Jan 2023). ### The bug ```python # src/diffusers/utils/torch_utils.py if isinstance(device, str): dev\u2026",
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    "body_excerpt": "## What does this PR do? Fixes the misleading error raised by `GGUFQuantizer.check_quantized_param_shape` when a loaded GGUF weight doesn't match the model's expected shape. ### Before ```python inferred_shape = _quant_shape_from_byte_shap\u2026",
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    "body_excerpt": "## What does this PR do? Closes #12504. `fourier_filter` (the FFT helper used by `enable_freeu`) already upcasts `bfloat16` inputs to `float32` before calling `torch.fft.fftn`, because PyTorch's FFT does not support bf16. The same is true\u2026",
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    "body_excerpt": "## Summary Two independent bugs that together prevent `use_stream=True` group offloading and context-parallel (ring/Ulysses) attention from working on **AMD ROCm** (tested on gfx1101 / RX 7800 XT, ROCm 7.1, PyTorch 2.7). Both fixes are bac\u2026",
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    "body_excerpt": "# What does this PR do? `VaeImageProcessor` exposes a `resample` config parameter (defaulting to `\"lanczos\"`) and correctly applies it when resizing **PIL images** via `PIL_INTERPOLATION`. However, the two `torch.nn.functional.interpolate`\u2026",
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    "body_excerpt": "# What does this PR do? Adds the modular pipeline for ErnieImage (`ErnieImageAutoBlocks` + `ErnieImageModularPipeline`). Parity verified on A100, bf16, 50 steps, 1024x1024 with `baidu/ERNIE-Image`: - MAD (AutoBlocks vs standard): 0.000033\u2026",
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    "body_excerpt": "## What does this PR do? Fixes two bugs in `PyramidAttentionBroadcastHook.new_forward`: **1. Redundant `iteration == 0` condition** After every `reset_state()`, both `iteration` and `cache` are reset to `0` and `None` respectively. So at i\u2026",
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    "body_excerpt": "This PR fixes failed test case: `tests/models/transformers/test_models_transformer_ernie_image.py::TestErnieImageTransformerCompile::test_torch_compile_repeated_blocks` @yiyixuxu pls help review, thx!",
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    "body_excerpt": "## Summary Fixes #13487 - `load_lora_weights` crashes with `AttributeError: 'Flux2ModularPipeline' object has no attribute 'transformer'` when called on a modular sub-pipeline that doesn't have the transformer component (e.g., a text-encod\u2026",
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    "body_excerpt": "## What does this PR do? Fixes two bugs in `PyramidAttentionBroadcastHook.new_forward`: 1. **Redundant `iteration == 0` condition** \u2014 `self.state.cache is None` already covers the first-call case after every `reset_state`, making the extra\u2026",
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    "body_excerpt": "## What does this PR do? Adds a monotonicity check to `LTXEulerAncestralRFScheduler.set_timesteps()` when an explicit sigma schedule is provided. **Bug:** When `sigmas` are supplied explicitly (ComfyUI-style), `set_timesteps()` accepts non\u2026",
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    "body_excerpt": "# What does this PR do? Fixes performance issues identified by profiling `ZImagePipeline` with `torch.profiler` as part of #13401 . ### What does this PR do? Profiled `ZImagePipeline` (using `Tongyi-MAI/Z-Image-Turbo`) in both eager and `t\u2026",
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    "body_excerpt": "# What does this PR do? This is to replicate what transformers already has: https://github.com/huggingface/transformers/blob/357f414cae88d5f592105bd97ec4a24ef7735f9f/src/transformers/dynamic_module_utils.py#L296-L310 from: https://github.c\u2026",
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    "body_excerpt": "# What does this PR do? Currently the behaviour/final module path of the are different in the following way: - if it's a standalone custom `AutoModel`, the dynamic module is being loaded directly from the hub into `diffusers_modules.local.\u2026",
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    "body_excerpt": "# What does this PR do? by using `get_class_obj_and_candidates`, this now can also check against custom components being passed in and not error out as not found. ##### side note I also noticed the second argument `library` from `maybe_rai\u2026",
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    "body_excerpt": "# What does this PR do? Cc: @bhavya01 and @entrpn. Could I get a review on this? From the [logs](https://pastebin.com/KmgxMgzm) and the generated image, seems like things are working as expected. <img width=\"1024\" height=\"1024\" alt=\"image\"\u2026",
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    "body_excerpt": "# What does this PR do? Fixes # (issue) change rope dtype from torch.float64 to torch.float32 to support more gpu backends.",
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    "body_excerpt": "## Problem The `--text_encoder_out_layers` CLI argument in `train_dreambooth_lora_flux2_klein.py` defaults to `[10, 20, 30]`, but the pipeline implementation (`pipeline_flux2_klein.py`) uses `(9, 18, 27)`. This off-by-one mismatch causes t\u2026",
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    "body_excerpt": "# What does this PR do? Fix https://github.com/huggingface/diffusers/actions/runs/24241815924/job/70778130709?pr=13332",
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    "title": "Fix SDXL Refiner with Higher Order Schedulers",
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    "body_excerpt": "This PR resolves the unsupported atten_mask shape error when running attention with NPU (Ascend) devices. Problem: The NPU\u2019s fusion attention operator (e.g., npu_fusion_attention) does not support automatic broadcasting for attention masks\u2026",
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    "body_excerpt": "# What does this PR do? `UniPCMultistepScheduler.set_timesteps` hardcodes `self.sigmas = self.sigmas.to(\"cpu\")` at the end of the method. This causes device mismatch errors in `multistep_uni_p_bh_update` and `multistep_uni_c_bh_update` whe\u2026",
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    "body_excerpt": "## Summary - Fix all 9 QwenImage pipeline variants where CFG is silently disabled when passing `negative_prompt_embeds` with `None` mask - `encode_prompt()` converts all-ones masks to `None` as an optimization (line 266-267), but `has_neg_\u2026",
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    "body_excerpt": "# What does this PR do? As per #13446 `trust_remote_code` fails under several circumstances: - `pretrained_model_name_or_path` as Hub repo A and `custom_pipeline` as Hub repo B, `trust_remote_code` is bypassed and remote code runs from rep\u2026",
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    "body_excerpt": "### Description **We are the JoyAI Team,** and this is the Diffusers implementation for the JoyAI-Image-Edit model. GitHub Repository: [https://github.com/jd-opensource/JoyAI-Image] Hugging Face Model: [https://huggingface.co/jdopensource/\u2026",
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    "body_excerpt": "# What does this PR do? Fixes the prior-preservation batching issue in the Qwen Image DreamBooth LoRA script. PR #13396 corrected the repeat count under `--with_prior_preservation`, but the script still repeats prompt embeddings with `repe\u2026",
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    "body_excerpt": "\u2026nstead of latent resolution # What does this PR do? Fixes #13439 prepare_cond_latents_and_mask shadows the pixel height/width parameters with latent dims from latents.shape (line 614): ``` batch, channels, frames, height, width = latents.\u2026",
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    "body_excerpt": "# What does this PR do? Adds an optional `decoder_block_out_channels` parameter to `AutoencoderKLFlux2` so the decoder can use different channel widths than the encoder. This is needed to support the FLUX.2 small decoder VAE (`black-forest\u2026",
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    "body_excerpt": "# What does this PR do? Fixes the use of `record_stream` with `torchao` and `group offload`. Without this, the resulting image is wrong. |Without this PR|With this PR| |---|---| |<img width=\"1024\" height=\"1024\" alt=\"flux_benchmark_dynamic_\u2026",
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    "body_excerpt": "# What does this PR do? This PR fixes a numerical stability issue in `rescale_noise_cfg` that can lead to division by zero and produce NaN/inf values during inference. ## Problem The current implementation performs: noise_pred_rescaled = n\u2026",
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    "body_excerpt": "# What does this PR do? Fixes https://github.com/huggingface/diffusers/actions/runs/24034864516/job/70092362359?pr=13417. Got missed in the earlier refactor.",
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    "body_excerpt": "## Summary - Fix `LoRA's` \u2192 `LoRAs` in two places (lines 104 and 106) - plural, not possessive - Fix `trigger it` \u2192 `trigger them` (pronoun agreement: \"Some LoRAs\" is plural) ## Changes **Line 104:** > Among adapters, [LoRA's] are the most\u2026",
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    "body_excerpt": "## What does this PR do? Fixes #13421 Adds `negative_prompt` parameter to `GLMImagePipeline.__call__()` and `encode_prompt()`. Previously, the unconditional prompt was hardcoded to `\"\"` when CFG was active, with no way for users to provide\u2026",
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    "body_excerpt": "## What does this PR do? Fixes #13416 Adds `negative_prompt` parameter to `Flux2KleinPipeline.__call__()`. Previously, the unconditional prompt was hardcoded to `\"\"` when CFG was active, with no way for users to provide a custom negative p\u2026",
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    "body_excerpt": "# What does this PR do? Fixes a device mismatch in the Flux2 DreamBooth training scripts when `--offload` is used and latents are not precomputed. non-cached path: `pixel_values` were converted to `vae.dtype` but not moved onto `accelerato\u2026",
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    "body_excerpt": "# What does this PR do? Fixes a prior-preservation batch size mismatch in the `Flux2 DreamBooth LoRA` scripts. When custom instance prompts are not used, `prompt_embeds` already contains concatenated instance + class embeddings under `--wi\u2026",
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    "body_excerpt": "## Summary - Fix article: `a inpainting` \u2192 `an inpainting` in auto_pipeline.py - Fix article: `a aesthetic_score` \u2192 `an aesthetic_score` in SDXL pipelines - Fix docstring: remove extraneous `pass a` in quantizers/base.py - Fix grammar: `al\u2026",
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    "body_excerpt": "## Summary - Fix `it's` \u2192 `its` (possessive form) in ~35 instances across ~32 model files - The phrase \"Check the superclass documentation for it's generic methods\" should use \"its\" (possessive), not \"it's\" (contraction of \"it is\") - Also\u2026",
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    "additions": 307,
    "author": "VittoriaLanzo",
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    "body_excerpt": "## What does this PR do? Fixes #13411. `LTXEulerAncestralRFScheduler.set_timesteps(sigmas=...)` silently accepted non-monotone sigma schedules. In `step()`, a reversed schedule computes: ``` downstep_ratio = 1 + (sigma_next / sigma - 1) *\u2026",
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    "additions": 46,
    "author": "yiyixuxu",
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    "body_excerpt": "follow https://github.com/huggingface/diffusers/pull/13334 moved `model-integrawtion/skillls/modular-conversion.md` to `.ai/modular.md`, and link it from `AGENTS.md`, `model-integrawtion/skillls` and `review-rules.md ` added a Gotcha secti\u2026",
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    "author": "awsr",
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    "body_excerpt": "# What does this PR do? Fixes `NameError: name 'ftfy' is not defined` This was encountered by one of our users on SDNext. I'm not entirely sure why `ftfy` didn't get installed, but if it's optionally imported then it should also be optiona\u2026",
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    "additions": 7,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary - Fix duplicate words: `schedule schedule` \u2192 `schedule`, `obtain obtain` \u2192 `obtain` - Fix article usage: `a image` \u2192 `an image` (2 instances), `a image-text` \u2192 `an image-text` (2 instances), `a upsampling` \u2192 `an upsampling` ## T\u2026",
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    "title": "fix: remove duplicate words and fix grammar in docstrings and error messages",
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    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary Add missing `f` prefix to ~50 string literals where variables like `{self.__class__}`, `{self.config}`, `{unet.config.*}`, `{type(...)}` are printed as literal text instead of being interpolated. ### Categories fixed: - Safety c\u2026",
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    "additions": 25,
    "author": "akshan-main",
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    "body_excerpt": "## What does this PR do? Part of #13401 `QwenEmbedRope.forward()` copies `pos_freqs` and `neg_freqs` from CPU to GPU via `.to(device)` on every transformer forward call. These tensors are fixed at init and never change, so the repeated tra\u2026",
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    "title": "Cache RoPE freqs on device to avoid repeated CPU-GPU copy in QwenImage",
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    "author": "andrewor14",
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    "body_excerpt": "**Summary:** TorchAO recently deprecated AffineQuantizedTensor and related classes (https://github.com/pytorch/ao/issues/2752). These will be removed in the next release. We should remove references of these classes in diffusers before the\u2026",
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    "author": "varaprasadtarunkumar",
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    "body_excerpt": "## What does this PR do? Fixes a per-step `torch.tensor()` reconstruction in `QwenImageTransformer2DModel.forward()` that was identified as a known performance issue in the [profiling guide](https://github.com/huggingface/diffusers/tree/ma\u2026",
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    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary - Add missing `f` prefix to 4 log messages in `bnb_quantizer.py` where `{target_dtype}` and `{current_device}` are printed as literal text instead of being interpolated - Affects both 4-bit and 8-bit BnB quantizer classes ## Tes\u2026",
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    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary - Fix 6 instances of `have have` \u2192 `have` in modular pipeline error messages - Fix `to to` \u2192 `to` in UNet docstring - Fix `be be` \u2192 `be` in Flux Kontext inpaint pipeline docstring ## Test plan - [ ] Verify error messages read co\u2026",
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    "title": "fix: remove duplicate words in error messages and docstrings",
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    "additions": 5,
    "author": "sayakpaul",
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    "title": "Update README.md of the profiling guide",
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    "author": "Ricardo-M-L",
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    "body_excerpt": "Two types of exception handling bugs: **1. `raise \"string\"` in attention_processor.py (lines 328-332)** \\`raise \"string\"\\` causes \\`TypeError: exceptions must derive from BaseException\\` at runtime instead of the intended error message. Ch\u2026",
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    "title": "improve Claude CI",
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    "additions": 4,
    "author": "chenyangzhu1",
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    "body_excerpt": "# What does this PR do? I found that the same problem in https://github.com/huggingface/diffusers/issues/13292 also appears in Qwen-Image's dreambooth lora script. https://github.com/huggingface/diffusers/blob/8070f6ec54a7699d5ee285090d973\u2026",
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    "title": "fix(qwen-image dreambooth): correct prompt embed repeats when using `--with_prior_preservation`",
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    "additions": 19,
    "author": "Akash504-ai",
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    "body_excerpt": "# What does this PR do? This PR fixes a missing validation in `DDPMScheduler.set_timesteps`. Currently, passing `num_inference_steps=0` does not raise an error and can lead to invalid internal state or unexpected behavior. This behavior is\u2026",
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    "title": "Fix missing validation for num_inference_steps in DDPMScheduler and add tests",
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    "author": "GalacticAvenger",
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    "body_excerpt": "## Summary Fixes several typos and grammar errors across the documentation: 1. **`controlling_generation.md`**: \"allows to generate\" \u2192 \"allows you to generate\" (missing object after \"allows\") 2. **`sdxl.md`**: \"it's refiner model\" \u2192 \"its r\u2026",
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    "title": "Fix typos and grammar errors in documentation",
    "updated_at": "2026-04-02T20:42:32Z"
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    "additions": 2070,
    "author": "RuixiangMa",
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    "body_excerpt": "# What does this PR do? Adds [LongCat-AudioDiT](https://github.com/meituan-longcat/LongCat-AudioDiT) model support to diffusers. Although LongCat-AudioDiT can be used for TTS-like generation, it is fundamentally a diffusion-based audio gen\u2026",
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    "title": "[Feat] Adds LongCat-AudioDiT pipeline ",
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    "body_excerpt": "## What does this PR do? Adds modular pipeline blocks for HunyuanVideo 1.5 with both text-to-video (`HunyuanVideo15Blocks`) and image-to-video (`HunyuanVideo15Image2VideoBlocks`). **Parity verified on Colab G4 GPU:** - T2V: MAD 0.000000 vs\u2026",
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    "title": "Add modular pipeline for HunyuanVideo 1.5",
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    "additions": 160,
    "author": "Ricardo-M-L",
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    "body_excerpt": "160 occurrences across 158 pipeline files use the incorrect phrase \"should be the same type to\" instead of \"should be the same type as\" in the negative_prompt type check error message. Example (before): ```python f\"`negative_prompt` should\u2026",
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    "body_excerpt": "# What does this PR do? When running the `train_dreambooth_lora_qwen_image.py `script with the `--with_prior_preservation` flag, the training crashes during the text embedding extraction phase. Fixing two distinct bugs related to tensor co\u2026",
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    "body_excerpt": "# What does this PR do? Currently everyone patches `_SET_ADAPTER_SCALE_FN_MAPPING` when training their models with peft https://github.com/search?q=_SET_ADAPTER_SCALE_FN_MAPPING&type=code Common patching practice looks like: ```python _SET\u2026",
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    "body_excerpt": "# What does this PR do? * Pytest's `caplog` fixture isn't enough to capture warnings and the errors raised from `src/diffusers/loaders/peft.py`. * Some QwenImage hotswapping tests are failing because of recompilation issues (which is known\u2026",
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    "body_excerpt": "# What does this PR do? This PR improves numerical stability for four custom autoencoder RMS normalization layers. For `fp16/bf16` inputs, normalization is computed in `fp32` and then cast back to the original dtype. These layers are imple\u2026",
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    "body_excerpt": "# What does this PR do? Fix https://github.com/huggingface/diffusers/issues/13311",
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    "title": "fix klein lora loading.",
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    "body_excerpt": "# What does this PR do? This PR expands the inputs of `QwenImage` UT from a single prompt to multiple prompts. Since `QwenImagePipeline` already supports multi-prompt inputs, we added corresponding test coverage here. - Tested with followi\u2026",
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    "title": "change QwenImageTransformer UT to batch inputs",
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    "body_excerpt": "## What does this PR do? Fixes #13298 When users pass a CUDA `torch.Generator` to diffusers pipelines, they may expect the same results as with a CPU generator given the same seed. However, PyTorch uses different random number generation a\u2026",
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    "body_excerpt": "## Summary Fixes silent weight corruption when loading models with `device_map=\"mps\"`. ### Root cause `load_model_dict_into_meta` unconditionally sets `non_blocking=True` for `set_module_tensor_to_device` (added for accelerate > 1.8.1). Wi\u2026",
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    "body_excerpt": "## Summary When `--with_prior_preservation` is enabled in the Flux2 dreambooth LoRA training scripts, the prompt embedding repeat logic double-counts the batch size, producing a shape mismatch against the latent tensor. **Root cause:** `co\u2026",
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    "body_excerpt": "--- What does this PR do? Adds a new documentation page for NeMo Automodel, NVIDIA's PyTorch DTensor-native training library for fine-tuning and pretraining diffusion models at scale. NeMo Automodel integrates directly with Diffusers \u2014 it\u2026",
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    "body_excerpt": "## What does this PR do? Fixes #13281. When combining torchao quantization (e.g. `Float8WeightOnlyConfig`) with group offloading (`use_stream=True`), inference fails with a device mismatch: the quantized weight remains on CPU while the inp\u2026",
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    "body_excerpt": "fix tests/models/transformers/test_models_transformer_flux.py::TestFluxTransformerContextParallel::test_context_parallel_inference[ulysses] tests/models/transformers/test_models_transformer_flux.py::TestFluxTransformerContextParallel::test\u2026",
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    "body_excerpt": "## Summary Adds support for the [DiffSynth-Studio blockwise ControlNet](https://github.com/modelscope/DiffSynth-Studio) architecture to the existing `QwenImageControlNetModel`, addressing [the maintainer's feedback on PR #12317](https://gi\u2026",
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    "author": "abhixb",
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    "body_excerpt": "Fixed issue #13177 ## The problem If you pass a tensor or numpy array as the image to the Klein pipeline, it errors even though the docstring explicitly says these types are supported. Three things cause this: - The image processor's valid\u2026",
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    "body_excerpt": "# What does this PR do? * Introduces `Flux2Transformer2DModelOutput` class as its outputs differ from the rest of the lot. * Test suite for Klein KV. * Docs.",
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    "body_excerpt": "Summary: Very brief writeup as I'm about to head out for the day: 1. we want to enable cuda graphs for qwen-image + nvfp4 at small batch sizes, because without cuda graphs are we bottlenecked on cpu ops 2. to make cuda graphs work, we need\u2026",
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    "body_excerpt": "# What does this PR do? Adds `Flux2KleinKVPipeline` \u2014 a KV-cached reference image conditioning pipeline for Flux2 Klein 9B. On the first denoising step, reference image tokens are included in the full transformer forward pass and their pos\u2026",
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    "body_excerpt": "## Summary Use safe dict access for alpha keys when converting non-diffusers Z-Image LoRA to diffusers format. Some LoRA formats use different alpha key naming (e.g. `layers.0.adaLN_modulation.0.alpha`), causing KeyError. ## Root Cause `st\u2026",
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    "title": "fix: use .get() for alpha keys in lora_conversion_utils.py",
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    "title": "Add AGENTS.md",
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    "body_excerpt": "# What does this PR do? This PR adds the `PRXPipeline` in the `AUTO_TEXT2IMAGE_PIPELINES_MAPPING`, so that PRX models e.g. https://huggingface.co/Photoroom/prx-1024-t2i-beta, can be loaded with the `AutoPipelineForText2Image` as it's curre\u2026",
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    "body_excerpt": "# What does this PR do? Fix https://github.com/huggingface/diffusers/issues/13249. @AlpineVibrations could you test if this is working?",
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    "title": "[lora] fix z-image non-diffusers lora loading.",
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    "body_excerpt": "@yiyixuxu and @asomoza, pls help review, thx! This PR fixes bug for following sample code: ``` import torch from diffusers import PaintByExamplePipeline from PIL import Image, ImageDraw # Load the pipeline pipe = PaintByExamplePipeline.fro\u2026",
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    "body_excerpt": "- Moves cosmos to the \"video\" model section - Updates the main example - Minor updates to docstrings in cosmos transfer2.5 pipeline Review: - Docs: @stevhliu and @sayakpaul",
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    "body_excerpt": "## Summary The `_convert_non_diffusers_z_image_lora_to_diffusers` function did not consume LoKr-format keys (`.lokr_w1`, `.lokr_w2`, `.alpha`) from external Z-image LoRA checkpoints (e.g. Kohya/LyCORIS), causing a `ValueError` when the sta\u2026",
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    "body_excerpt": "a few maintenance items: - move \"Guiders\" out of Modular Diffusers (because its not exclusive to it). i think after \"Schedulers\" is the most logical place for guiders as they're both swappable components and it has a much higher visibility\u2026",
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    "body_excerpt": "# What does this PR do? Implements a test suite for the conditional blocks for the following functionalities: * `get_workflow()` works as expected. * `select_blocks()` works as expected. * Automatic workflow selection works as expected. Th\u2026",
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    "title": "[tests] Tests for conditional pipeline blocks",
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    "body_excerpt": "# What does this PR do? Fixes a bug where `sigma_min` and `sigma_max` were computed from already-shifted sigmas in `__init__`, causing `set_timesteps()` to apply the shift formula twice. Fixes #13243 ## Root cause In `__init__`, the shift\u2026",
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    "title": "Fix double-shifted sigma_min/sigma_max in FlowMatchEulerDiscreteScheduler",
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    "body_excerpt": "# What does this PR do? Add tests (two tests: loading from a modular repo and loading from a local path) to ensure `load_components()` always loads the expected components. Here, I took the liberty of defining `expected_components` as the\u2026",
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    "body_excerpt": "## Summary Fixes #12771 \u2014 `DPMSolverMultistepScheduler` crashes with `IndexError: index 21 is out of bounds for dimension 0 with size 21` when using `beta_schedule='squaredcos_cap_v2'` with `use_karras_sigmas=True`. ## Root Cause When usin\u2026",
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    "body_excerpt": "## What does this PR do? Fixes #12771 \u2014 `DPMSolverMultistepScheduler` crashes with `IndexError: index N is out of bounds` when using `beta_schedule='squaredcos_cap_v2'` with `use_karras_sigmas=True` (or `use_lu_lambdas=True`). ### Root cau\u2026",
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    "body_excerpt": "## Description In `_offload_to_memory()`, when using CUDA streams (`self.stream is not None`), module buffers from `self.modules` were not being restored to their CPU tensor copies during offload. This created an asymmetry with both `_buil\u2026",
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    "body_excerpt": "# What does this PR do? It enables detection of FLUX.2 Klein models when loading transformers from single file, like in the following example: ```python import torch from diffusers import Flux2KleinPipeline, Flux2Transformer2DModel, GGUFQu\u2026",
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    "body_excerpt": "# What does this PR do? I believe that the error message was wrong, since the shapes mentionned did not match the test trigering the error. I think that there is also an ambiguity on what is meant by \"quantized\" shape: the value returned b\u2026",
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    "body_excerpt": "# What does this PR do? - [x] Refactor MagCache tests. - [x] Include TaylorSeer in our model-level caching test mixin. - [ ] Consider removing caching-related mixins from `test_pipelines_common.py`.",
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    "body_excerpt": "Potential fix for [https://github.com/huggingface/diffusers/security/code-scanning/2147](https://github.com/huggingface/diffusers/security/code-scanning/2147) In general, the fix is to explicitly set a `permissions` block in the workflow (\u2026",
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    "body_excerpt": "# What does this PR do? This PR adds support for [Diffusion Transformers with Representation Autoencoders](https://rae-dit.github.io) in Diffusers. It implements the Stage-2 side of the RAE setup: - `RAEDiT2DModel` - `RAEDiTPipeline` - che\u2026",
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    "body_excerpt": "This PR adds LTX-VAE support for SANA-Video. Cc: @dg845 @sayakpaul GPU memory needed: 47GB for LTX refiner ### SANA-Video with LTX2-Refiner: ```python \"\"\"Sana Video + LTX2 Refiner: Stage 1 generate latent \u2192 Stage 2 refine (3 steps).\"\"\" imp\u2026",
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    "body_excerpt": "Allow pass cpu generator for helios. w/o this fix, helios distilled pipeline will raise an device mismatch error if we use cpu generator. we should use the device from generator for torch.randn. ```bash File \"/workspace/deftruth/dev/minico\u2026",
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    "body_excerpt": "cc @dg845 @sayakpaul @yiyixuxu ### Helios-Distilled ``` # CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun --master_port 12311 --nproc_per_node 2 infer_distilled.py import os import argparse import torch import torch.distributed as dist from diffuser\u2026",
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    "body_excerpt": "# What does this PR do? This PR refactors `AttentionProcessorSkipHook` to support attention processors with a `_skip_attn_scores` flag, which is meant to allow attention processors to specify custom [spatio-temporal guidance (STG)](https:/\u2026",
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    "body_excerpt": "# What does this PR do? This PR fixes wrapped transformer config access in the Flux2 Klein DreamBooth LoRA training scripts. When the transformer is wrapped by Accelerate, DDP, or FSDP, accessing `transformer.config.guidance_embeds` direct\u2026",
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    "body_excerpt": "In helios pipeline, the latents are always in FP32 format: [L798](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/helios/pipeline_helios.py#L798), hence we should skip the test_save_load_float16 test case, rather\u2026",
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    "body_excerpt": "```py import torch from diffusers import ModularPipeline, ClassifierFreeGuidance, ClassifierFreeZeroStarGuidance from diffusers.utils import export_to_video, load_image, load_video import gc branch = \"\" ############################# # heli\u2026",
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    "title": "Fix Helios paper link in documentation",
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    "body_excerpt": "Just an extension of #13183 to the other Z-Image pipleines @yiyixuxu @sayakpaul",
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    "title": "[Z-Image] Fix more `do_classifier_free_guidance` thresholds",
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    "body_excerpt": "Related to https://github.com/huggingface/diffusers/pull/13208 and https://github.com/huggingface/diffusers/pull/13210 cc @yiyixuxu cc @sayakpaul cc @dg845",
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    "title": "Fix group-offloading bug",
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    "title": "Fix Helios related (optimize docs & remove redudant)",
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    "body_excerpt": "# What does this PR do? Fixes https://github.com/huggingface/diffusers/issues/13203 Additionally, fixes how \"alpha\"s are handled in the diffusers format path.",
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    "title": "[lora] fix zimage lora conversion to support for more lora.",
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    "author": "dg845",
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    "body_excerpt": "# What does this PR do? This PR adds pipelines for the Helios-14B video generation model ([project page](https://pku-yuangroup.github.io/Helios-Page/), [official code](https://github.com/PKU-YuanGroup/Helios), [model weights](https://huggi\u2026",
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    "author": "jiqing-feng",
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    "body_excerpt": "Currently, every process encodes the entire dataset through the VAE during preprocessing. This is redundant in multi-GPU training \u2014 each process does the same full encoding work independently. This PR shards the VAE encoding across process\u2026",
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    "title": "cogvideo example: Distribute VAE video encoding across processes in CogVideoX LoRA training",
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    "author": "kirillsst",
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    "body_excerpt": "## Summary - Add `scheduler.set_begin_index(0)` before the denoising loop in all flow-matching pipelines that were missing it - For img2img pipelines with strength-based schedule truncation (`wan_video2video`, `ltx_condition`), set the beg\u2026",
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    "author": "teith",
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    "body_excerpt": "# What does this PR do? Fixes invalid type annotation for the `image` parameter in `Flux2Pipeline.__call__`. `list[PIL.Image.Image, PIL.Image.Image]` passes two type arguments to `list`, which only accepts one. Fixed to `PIL.Image.Image |\u2026",
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    "body_excerpt": "based on this discussion https://github.com/huggingface/blog/pull/3278#discussion_r2873972272",
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    "title": "[modular] not pass trust_remote_code to external repos ",
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    "author": "DN6",
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    "body_excerpt": "# What does this PR do? Accidentally committed a bunch of extra Claude files. Removing them here. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes\u2026",
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    "body_excerpt": "Reverts huggingface/diffusers#13168",
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    "title": "Revert \"[Modular] Save Modular Pipeline weights to Hub\"",
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    "author": "christopher5106",
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    "body_excerpt": "If you don't see any problem having Lora support for Controlnet pipelines for Z-Image, here is the PR. @sayakpaul",
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    "title": "adding lora support to z-image controlnet pipelines",
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    "body_excerpt": "# What does this PR do? Remove DB utils from the benchmarking workflow. Internal thread: https://huggingface.slack.com/archives/CTKK32GE8/p1772345661280549 Cc: @McPatate",
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    "title": "remove db utils from benchmarking",
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    "author": "delmalih",
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    "body_excerpt": "# What does this PR do? This PR improves the docstrings and type hints in `src/diffusers/schedulers/scheduling_ipndm.py` to follow the project conventions as described in #9567. ## Context This is part of a broader effort to improve docume\u2026",
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    "body_excerpt": "# What does this PR do? When loading custom code from a local path with AutoModel, the subfolder argument is not properly handled in `get_cached_module_file`. This results in this check for a valid file path failing and a local path being\u2026",
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    "body_excerpt": "before https://huggingface.co/YiYiXu/modular-loader-t2i-0704 after https://huggingface.co/YiYiXu/modular-loader-t2i-20260227 the input/output isn't too meaningful for conditional/auto pipeline so it is better we show them for each workflow\u2026",
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    "body_excerpt": "# What does this PR do? Why not use `pytest` features haha.",
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    "body_excerpt": "so that we are able to correctly load repos like https://huggingface.co/diffusers/flux2-modular When creating a pipeline using `SequentialPipelineBlocks.from_blocks_dict()` and saving it, the `modular_model_index.json` stores `_blocks_clas\u2026",
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    "body_excerpt": "# What does this PR do? `modular_model_index.json` is a fundamental block for sharing and loading modular blocks and pipelines. This PR adds a test to ensure the integrity and consistency of a `modular_model_index.json`. I think this will\u2026",
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    "body_excerpt": "## What does this PR do? Fixes None dereference crashes and a mutable default argument bug: **1. `models/model_loading_utils.py`** - `_fetch_remapped_cls_from_config` used chained `.get().get()` without a fallback on the first call. If `pr\u2026",
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    "body_excerpt": "I added support for Kohya's Flux.2 loras to the PR as well. Reproducer code is: FLUX.2 Dev ```python import torch from diffusers import Flux2Pipeline pipe = Flux2Pipeline.from_pretrained(\"black-forest-labs/FLUX.2-dev\", torch_dtype=torch.bf\u2026",
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    "body_excerpt": "## What does this PR do? Fixes several latent bugs across the codebase: **Mutable default arguments** (shared state across calls): - `_replace_with_gguf_linear`: `modules_to_not_convert=[]` -> `None` with guard - `_dequantize_gguf_and_rest\u2026",
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    "body_excerpt": "## Summary - Z-Image uses a different CFG formula: `pred = pos + guidance_scale * (pos - neg)`, where `guidance_scale = 0` corresponds to no guidance - The `do_classifier_free_guidance` property was checking `> 1` (standard diffusers conve\u2026",
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    "body_excerpt": "# What does this PR do? * Fixes support for ring attention for Flash and Flash 3 * Adds a test suite for CP backends x attention backends <img width=\"1024\" height=\"1024\" alt=\"image\" src=\"https://github.com/user-attachments/assets/2600632f-\u2026",
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    "body_excerpt": "# What does this PR do? Since Quanto is now in maintenance mode. I think we can deprecate it and remove by 1.0.0 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in th\u2026",
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    "body_excerpt": "## Summary Closes #13104 Issue #13104 reports a `NameError: name 'logger' is not defined` that occurs at import time when `_update_torch_safe_globals()` in `torchao_quantizer.py` raises an `ImportError` (e.g. when `torchao.dtypes.uintx.uin\u2026",
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    "body_excerpt": "After [Dao-AILab/flash-attention@ed20940](https://github.com/Dao-AILab/flash-attention/commit/ed209409acedbb2379f870bbd03abce31a7a51b7), `flash_attn_3_func` no longer returns `(out, lse, ...)` by default -- it just returns `out`. This brea\u2026",
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    "body_excerpt": "# What does this PR do? Now that the Hub-based attention backends (Flash, Flash 3, SAGE) have been fully feature-complete (`torch.compile`, CP, etc.), we can confidently remove the non-Hub variants. This has several advantages: * More Hub-\u2026",
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