[Tutorial] "Fine Tuning" Stable Diffusion using only 5 Images Using Textual Inversion.

This page summarizes the projects mentioned and recommended in the original post on /r/StableDiffusion

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  • textual_inversion

  • Go to the textual_inversion repository link here

  • stable-diffusion

    Discontinued This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI] (by lstein)

  • Find SIGUSR1 (& 2), and change it to SIGTERM.. Can also recommend lstein's fork, which is Stable Diffusion with a "Dream" Prompt and Textual Inversion built in https://github.com/lstein/stable-diffusion

  • InfluxDB

    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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  • stable-diffusion-dream

    Discontinued This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface.

  • or a fork based on lstein that sometimes has some branches with new stuff, but they're pretty even at the moment. https://github.com/BaristaLabs/stable-diffusion-dream

  • yolov3

    YOLOv3 in PyTorch > ONNX > CoreML > TFLite

  • Hey. I only have experience using the official repository, and only use Linux. Could you try the solutions here and see if it helps? https://github.com/ultralytics/yolov3/issues/1643

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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