GitLab

* working state from hameerabbasi and iddl

* working state form hameerabbasi and iddl (transformer)

* working state (normalization)

* working state (embeddings)

* add chroma loader

* add chroma to mappings

* add chroma to transformer init

* take out variant stuff

* get decently far in changing variant stuff

* add chroma init

* make chroma output class

* add chroma transformer to dummy tp

* add chroma to init

* add chroma to init

* fix single file

* update

* update

* add chroma to auto pipeline

* add chroma to pipeline init

* change to chroma transformer

* take out variant from blocks

* swap embedder location

* remove prompt_2

* work on swapping text encoders

* remove mask function

* dont modify mask (for now)

* wrap attn mask

* no attn mask (can't get it to work)

* remove pooled prompt embeds

* change to my own unpooled embeddeer

* fix load

* take pooled projections out of transformer

* ensure correct dtype for chroma embeddings

* update

* use dn6 attn mask + fix true_cfg_scale

* use chroma pipeline output

* use DN6 embeddings

* remove guidance

* remove guidance embed (pipeline)

* remove guidance from embeddings

* don't return length

* dont change dtype

* remove unused stuff, fix up docs

* add chroma autodoc

* add .md (oops)

* initial chroma docs

* undo don't change dtype

* undo arxiv change

unsure why that happened

* fix hf papers regression in more places

* Update docs/source/en/api/pipelines/chroma.md
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* do_cfg -> self.do_classifier_free_guidance

* Update docs/source/en/api/models/chroma_transformer.md
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update chroma.md

* Move chroma layers into transformer

* Remove pruned AdaLayerNorms

* Add chroma fast tests

* (untested) batch cond and uncond

* Add # Copied from for shift

* Update # Copied from statements

* update norm imports

* Revert cond + uncond batching

* Add transformer tests

* move chroma test (oops)

* chroma init

* fix chroma pipeline fast tests

* Update src/diffusers/models/transformers/transformer_chroma.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Move Approximator and Embeddings

* Fix auto pipeline + make style, quality

* make style

* Apply style fixes

* switch to new input ids

* fix # Copied from error

* remove # Copied from on protected members

* try to fix import

* fix import

* make fix-copes

* revert style fix

* update chroma transformer params

* update chroma transformer approximator init params

* update to pad tokens

* fix batch inference

* Make more pipeline tests work

* Make most transformer tests work

* fix docs

* make style, make quality

* skip batch tests

* fix test skipping

* fix test skipping again

* fix for tests

* Fix all pipeline test

* update

* push local changes, fix docs

* add encoder test, remove pooled dim

* default proj dim

* fix tests

* fix equal size list input

* update

* push local changes, fix docs

* add encoder test, remove pooled dim

* default proj dim

* fix tests

* fix equal size list input

* Revert "fix equal size list input"

This reverts commit 3fe4ad67d58d83715bc238f8654f5e90bfc5653c.

* update

* update

* update

* update

* update

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Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

update

* update

* update

* update

* update

* update

* update

* update

* Fix typos in docs and comments

* Apply style fixes

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* enable telemetry for single file loading when using GGUF.

* quality

update

* Fixed requests.get function call by adding timeout parameter.

* declare DIFFUSERS_REQUEST_TIMEOUT in constants and import when needed

* remove unneeded os import

* Apply style fixes

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Co-authored-by: Sai-Suraj-27 <sai.suraj.27.729@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* added support for from_single_file

* added diffusers mapping script

* added testcase

* bug fix

* updated tests

* corrected code quality

* corrected code quality

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Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* update

* update

* update

* update

* update

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* update

update

* Fix SD2.X clip single file load projection_dim

Infer projection_dim from the checkpoint before loading
from pretrained, override any incorrect hub config.

Hub configuration for SD2.X specifies projection_dim=512
which is incorrect for SD2.X checkpoints loaded from civitai
and similar.

Exception was previously thrown upon attempting to
load_model_dict_into_meta for SD2.X single file checkpoints.

Such LDM models usually require projection_dim=1024

* convert_open_clip_checkpoint use hidden_size for text_proj_dim

* convert_open_clip_checkpoint, revert checkpoint[text_proj_key].shape[1] -> [0]

values are identical

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Co-authored-by: Teriks <Teriks@users.noreply.github.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* first draft model loading refactor

* revert name change

* fix bnb

* revert name

* fix dduf

* fix huanyan

* style

* Update src/diffusers/models/model_loading_utils.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* suggestions from reviews

* Update src/diffusers/models/modeling_utils.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* remove safetensors check

* fix default value

* more fix from suggestions

* revert logic for single file

* style

* typing + fix couple of issues

* improve speed

* Update src/diffusers/models/modeling_utils.py
Co-authored-by: Aryan <aryan@huggingface.co>

* fp8 dtype

* add tests

* rename resolved_archive_file to resolved_model_file

* format

* map_location default cpu

* add utility function

* switch to smaller model + test inference

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* rm comment

* add log

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add decorator

* cosine sim instead

* fix use_keep_in_fp32_modules

* comm

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>

* update

* update

change licensing to 2025 from 2024.

* update

* update

* update

* update

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Add a `disable_mmap` option to the `from_single_file` loader to improve load performance on network mounts (#10305)

* Add no_mmap arg.

* Fix arg parsing.

* Update another method to force no mmap.

* logging

* logging2

* propagate no_mmap

* logging3

* propagate no_mmap

* logging4

* fix open call

* clean up logging

* cleanup

* fix missing arg

* update logging and comments

* Rename to disable_mmap and update other references.

* [Docs] Update ltx_video.md to remove generator from `from_pretrained()` (#10316)

Update ltx_video.md to remove generator from `from_pretrained()`

* docs: fix a mistake in docstring (#10319)

Update pipeline_hunyuan_video.py

docs: fix a mistake

* [BUG FIX] [Stable Audio Pipeline] Resolve torch.Tensor.new_zeros() TypeError in function prepare_latents caused by audio_vae_length (#10306)

[BUG FIX] [Stable Audio Pipeline] TypeError: new_zeros(): argument 'size' failed to unpack the object at pos 3 with error "type must be tuple of ints,but got float"

torch.Tensor.new_zeros() takes a single argument size (int...) – a list, tuple, or torch.Size of integers defining the shape of the output tensor.

in function prepare_latents:
audio_vae_length = self.transformer.config.sample_size * self.vae.hop_length
audio_shape = (batch_size // num_waveforms_per_prompt, audio_channels, audio_vae_length)
...
audio = initial_audio_waveforms.new_zeros(audio_shape)

audio_vae_length evaluates to float because self.transformer.config.sample_size returns a float
Co-authored-by: hlky <hlky@hlky.ac>

* [docs] Fix quantization links (#10323)

Update overview.md

* [Sana]add 2K related model for Sana (#10322)

add 2K related model for Sana

* Update src/diffusers/loaders/single_file_model.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/loaders/single_file.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* make style

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Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Leojc <liao_junchao@outlook.com>
Co-authored-by: Aditya Raj <syntaxticsugr@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Junsong Chen <cjs1020440147@icloud.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Add support for loading AuraFlow models from GGUF

https://huggingface.co/city96/AuraFlow-v0.3-gguf



* Update AuraFlow documentation for GGUF, add GGUF tests and model detection.

* Address code review comments.

* Remove unused config.

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Co-authored-by: hlky <hlky@hlky.ac>

* Add torch_xla and from_single_file to instruct-pix2pix

* StableDiffusionInstructPix2PixPipelineSingleFileSlowTests

* StableDiffusionInstructPix2PixPipelineSingleFileSlowTests

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

* update

* make style

* update

* update

* update

* make style

* single file related changes

* update

* fix

* update single file urls and docs

* update

* fix

update

* update

* Update src/diffusers/loaders/single_file_utils.py
Co-authored-by: Aryan <aryan@huggingface.co>

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Co-authored-by: Aryan <aryan@huggingface.co>

* update

* add docs.

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

update

update

* update

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* Update src/diffusers/quantizers/gguf/utils.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* Update docs/source/en/quantization/gguf.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* update

* update

* update

* update

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* transformer

* make style & make fix-copies

* transformer

* add transformer tests

* 80% vae

* make style

* make fix-copies

* fix

* undo cogvideox changes

* update

* update

* match vae

* add docs

* t2v pipeline working; scheduler needs to be checked

* docs

* add pipeline test

* update

* update

* make fix-copies

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* update

* copy t2v to i2v pipeline

* update

* apply review suggestions

* update

* make style

* remove framewise encoding/decoding

* pack/unpack latents

* image2video

* update

* make fix-copies

* update

* update

* rope scale fix

* debug layerwise code

* remove debug

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* propagate precision changes to i2v pipeline

* remove downcast

* address review comments

* fix comment

* address review comments

* [Single File] LTX support for loading original weights (#10135)

* from original file mixin for ltx

* undo config mapping fn changes

* update

* add single file to pipelines

* update docs

* Update src/diffusers/models/autoencoders/autoencoder_kl_ltx.py

* Update src/diffusers/models/autoencoders/autoencoder_kl_ltx.py

* rename classes based on ltx review

* point to original repository for inference

* make style

* resolve conflicts correctly

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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* update

* update

* update

update

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* update

* update

* update

* update

* update

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* update sd15 repo

* update more

update to a place holder

update

update

* allow sparsectrl to be loaded with single file

* update

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Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* update

* update

* update

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* remove resume_download

* fix: _fetch_index_file call.

* remove resume_download from docs.