Dreambooth able to run on 18GB VRAM now. Potentially on 16GB in the future with more optimization.

• diffusers

  105 1,868 7.0 Python

  🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch (by ShivamShrirao)

Repo located here: https://github.com/ShivamShrirao/diffusers/tree/main/examples/dreambooth

• xformers

  46 7,473 9.4 Python

  Hackable and optimized Transformers building blocks, supporting a composable construction.

  

Stable Diffusion dreambooth training in just 17.7GB GPU usage by replacing the attention with memory efficient flash attention from xformers. Along with using way less memory, it also runs 2 times faster. So it's possible to train SD in 24GB GPUs now.

• WorkOS

  workos.com sponsored

  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

• nvtop

  41 7,365 8.1 C

  GPU & Accelerator process monitoring for AMD, Apple, Huawei, Intel, NVIDIA and Qualcomm

• Dreambooth-Stable-Diffusion

  100 3,161 6.8 Jupyter Notebook

  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)

I tried the fork of JoePenna, there is a notebook with all required step but it's tailored for another GPU cloud rental architecture. I didn't manage to make it work but you can give it a try

• Pytorch

  334 77,544 10.0 Python

  Tensors and Dynamic neural networks in Python with strong GPU acceleration

  

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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