I've been collecting millions of images of only public domain /cc0 licensing. I'd like to train a stable diffusion model on the collection. Could some one share their knowledge of what this would take? Otherwise, simply enjoy my library.

• kohya_ss

  132 8,362 9.9 Python

• EveryDream

  13 219 3.3 Python

  Advanced fine tuning tools for vision models

In terms of training, you've got some really good links and comments to youtube tutorials, but if you're interested in more information about finetuning a model (as opposed to training from scratch), this is a good repo that has a lot of tools for finetuning, including an auto-captioner using BLIP and automatic file renaming. This is the actual finetuning repo.

• InfluxDB

  www.influxdata.com featured

  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.

  

• EveryDream-trainer

  32 501 2.4 Jupyter Notebook

  General fine tuning for Stable Diffusion

In terms of training, you've got some really good links and comments to youtube tutorials, but if you're interested in more information about finetuning a model (as opposed to training from scratch), this is a good repo that has a lot of tools for finetuning, including an auto-captioner using BLIP and automatic file renaming. This is the actual finetuning repo.

• kohya-trainer

  36 1,772 8.3 Jupyter Notebook

  Discontinued Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning

Here is another repo for finetuning models, as well as finetuning Loras - this is the one I used to train a Lora.

• latent-diffusion

  70 10,681 0.0 Jupyter Notebook

  High-Resolution Image Synthesis with Latent Diffusion Models

  

CompVis/latent-diffusion: High-Resolution Image Synthesis with Latent Diffusion Models (github.com)

• SaaSHub

  www.saashub.com featured

  SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

  

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