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Xformers Alternatives
Similar projects and alternatives to xformers
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Judoscale
Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
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diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
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InvokeAI
Invoke is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, and serves as the foundation for multiple commercial products.
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diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch (by ShivamShrirao)
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InfluxDB
InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
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Dreambooth-Stable-Diffusion
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles. (by JoePenna)
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lucide
Beautiful & consistent icon toolkit made by the community. Open-source project and a fork of Feather Icons.
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pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
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MiDaS
Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"
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Dreambooth-Stable-Diffusion
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
xformers discussion
xformers reviews and mentions
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Practical Experience: Integrating Over 50 Neural Networks Into One Open-Source Project
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.
- An Interview with AMD CEO Lisa Su About Solving Hard Problems
- Animediff error
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Colab | Errors when installing x-formers
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
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FlashAttention-2, 2x faster than FlashAttention
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
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Xformers issue
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
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Having xformer troubles
ModuleNotFoundError: Refer to https://github.com/facebookresearch/xformers for more
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Question: these 4 crappy picture have been generated with the same seed and settings. Why they keep coming mildly different?
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:
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Stuck trying to update 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. =================================================================================
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Question about updating Xformers for A1111
# 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.
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A note from our sponsor - Judoscale
judoscale.com | 30 Apr 2025
Stats
facebookresearch/xformers is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of xformers is Python.
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