xformers VS diffusers

Check xformers Compatibility Visit the xformers GitHub repo to ensure compatibility with your torch and CUDA versions. Support for older versions can be dropped, so staying updated is vital, especially if you're running CUDA 11.8 and want to leverage xformers for limited VRAM.

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. fastai 2.7.12 requires torch<2.1,>=1.7, but you have torch 2.1.0+cu118 which is incompatible. torchaudio 2.0.2+cu118 requires torch==2.0.1, but you have torch 2.1.0+cu118 which is incompatible. torchdata 0.6.1 requires torch==2.0.1, but you have torch 2.1.0+cu118 which is incompatible. torchtext 0.15.2 requires torch==2.0.1, but you have torch 2.1.0+cu118 which is incompatible. torchvision 0.15.2+cu118 requires torch==2.0.1, but you have torch 2.1.0+cu118 which is incompatible. WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for: PyTorch 2.1.0+cu121 with CUDA 1201 (you have 2.1.0+cu118) Python 3.10.13 (you have 3.10.12) Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers) Memory-efficient attention, SwiGLU, sparse and more won't be available. Set XFORMERS_MORE_DETAILS=1 for more details xformers version: 0.0.22.post3

This enables V1. V2 is still yet to be integrated into xformers. The team replied saying it should happen this week.

See the relevant Github issue here: https://github.com/facebookresearch/xformers/issues/795

My Xformers doesnt work, any help see code. info ( Exception training model: 'Refer to https://github.com/facebookresearch/xformers for more information on how to install xformers'. ) or

ModuleNotFoundError: Refer to https://github.com/facebookresearch/xformers for more

Xformers is a module that that can be used with Stable Diffusion. It decreases the memory required to generate an image as well as speeding things up. It works very well but there are two problems with Xformers:

WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for: PyTorch 1.13.1+cu117 with CUDA 1107 (you have 2.0.1+cu118) Python 3.10.9 (you have 3.10.7) Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers) Memory-efficient attention, SwiGLU, sparse and more won't be available. Set XFORMERS_MORE_DETAILS=1 for more details ================================================================================= You are running xformers 0.0.16rc425. The program is tested to work with xformers 0.0.17. To reinstall the desired version, run with commandline flag --reinstall-xformers. Use --skip-version-check commandline argument to disable this check. =================================================================================

# Your version of xformers is 0.0.16rc425. # xformers >= 0.0.17.dev is required to be available on the Dreambooth tab. # Torch 1 wheels of xformers >= 0.0.17.dev are no longer available on PyPI, # but you can manually download them by going to: https://github.com/facebookresearch/xformers/actions # Click on the most recent action tagged with a release (middle column). # Select a download based on your environment. # Unzip your download # Activate your venv and install the wheel: (from A1111 project root) cd venv/Scripts activate pip install {REPLACE WITH PATH TO YOUR UNZIPPED .whl file} # Then restart your project.

ShivamShrirao's Diffusers Pretrained diffusion models across multiple modalities.

Like the title say I'm trying to fine-tune a model to match a style of a popular manhwa. I'm using the ShivamShrirao Google Colab to accomplish this.

I am running the DreamBooth_Stable_Diffusion.ipynb notebook from ShivamShrirao locally on my machine. Let's say I have trained for 500 iterations and it hasn't converged yet. How do I make it resume training from that iteration so it can do another 500?

My understanding, based on messages from an (alleged) representative of colabs, is that the webui is the problem, not SD itself. This also seems to be the consensus in the comments section of other posts. I have not yet seen a link to colab based webui alternatives so here is something I found from a tutorial. I am certain that there are better alternatives. Anyone have a better idea? This will still probably be useful to other people like me who are just messing around.

I'm running ShivamShrirao's fork of diffusers; ran into a fp16 issue and had to patch in a fix from the main branch ( #1567 ).

I am running Shivam Stable Diffusion Jupyter notebook: diffusers/DreamBooth_Stable_Diffusion.ipynb at main · ShivamShrirao/diffusers · GitHub.

Are you using this one? https://github.com/S