mirror of
https://github.com/huggingface/diffusers.git
synced 2026-06-05 00:53:09 +08:00
Some checks failed
Build documentation / build (push) Has been cancelled
CodeQL Security Analysis For Github Actions / CodeQL Analysis (push) Has been cancelled
Run dependency tests / check_dependencies (push) Has been cancelled
Run Torch dependency tests / check_torch_dependencies (push) Has been cancelled
Fast GPU Tests on main / Setup Torch Pipelines CUDA Slow Tests Matrix (push) Has been cancelled
Fast GPU Tests on main / Torch Pipelines CUDA Tests (push) Has been cancelled
Fast GPU Tests on main / Torch CUDA Tests (lora) (push) Has been cancelled
Fast GPU Tests on main / Torch CUDA Tests (models) (push) Has been cancelled
Fast GPU Tests on main / Torch CUDA Tests (others) (push) Has been cancelled
Fast GPU Tests on main / Torch CUDA Tests (schedulers) (push) Has been cancelled
Fast GPU Tests on main / Torch CUDA Tests (single_file) (push) Has been cancelled
Fast GPU Tests on main / PyTorch Compile CUDA tests (push) Has been cancelled
Fast GPU Tests on main / PyTorch xformers CUDA tests (push) Has been cancelled
Fast GPU Tests on main / Examples PyTorch CUDA tests on Ubuntu (push) Has been cancelled
Fast tests on main / Fast PyTorch CPU tests on Ubuntu (push) Has been cancelled
Fast tests on main / PyTorch Example CPU tests on Ubuntu (push) Has been cancelled
Secret Leaks / trufflehog (push) Has been cancelled
Update Diffusers metadata / update_metadata (push) Has been cancelled
* feat: implement three RAE encoders(dinov2, siglip2, mae) * feat: finish first version of autoencoder_rae * fix formatting * make fix-copies * initial doc * fix latent_mean / latent_var init types to accept config-friendly inputs * use mean and std convention * cleanup * add rae to diffusers script * use imports * use attention * remove unneeded class * example traiing script * input and ground truth sizes have to be the same * fix argument * move loss to training script * cleanup * simplify mixins * fix training script * fix entrypoint for instantiating the AutoencoderRAE * added encoder_image_size config * undo last change * fixes from pretrained weights * cleanups * address reviews * fix train script to use pretrained * fix conversion script review * latebt normalization buffers are now always registered with no-op defaults * Update examples/research_projects/autoencoder_rae/README.md Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * Update src/diffusers/models/autoencoders/autoencoder_rae.py Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * use image url * Encoder is frozen * fix slow test * remove config * use ModelTesterMixin and AutoencoderTesterMixin * make quality * strip final layernorm when converting * _strip_final_layernorm_affine for training script * fix test * add dispatch forward and update conversion script * update training script * error out as soon as possible and add comments * Update src/diffusers/models/autoencoders/autoencoder_rae.py Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com> * use buffer * inline * Update src/diffusers/models/autoencoders/autoencoder_rae.py Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com> * remove optional * _noising takes a generator * Update src/diffusers/models/autoencoders/autoencoder_rae.py Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com> * fix api * rename * remove unittest * use randn_tensor * fix device map on multigpu * check if the key is missing in the original state dict and only then add to the allow_missing set * remove initialize_weights --------- Co-authored-by: wangyuqi <wangyuqi@MBP-FJDQNJTWYN-0208.local> Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
Research projects
This folder contains various research projects using 🧨 Diffusers. They are not really maintained by the core maintainers of this library and often require a specific version of Diffusers that is indicated in the requirements file of each folder. Updating them to the most recent version of the library will require some work.
To use any of them, just run the command
pip install -r requirements.txt
inside the folder of your choice.
If you need help with any of those, please open an issue where you directly ping the author(s), as indicated at the top of the README of each folder.