Question About Running Local Textual Inversion

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

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  • stylegan2-projecting-images

    Projecting images to latent space with StyleGAN2.

  • Attempting to connect gives me a "Blocking Cross Origin API request for /http_over_websocket. Origin: https://colab.research.google.com, Host: localhost:8888" error. I have no idea what this means, as the port is open.

  • diffusers

    🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

  • If you are using the diffusers version locally, it's broken and needs a fix currently. It will train, output an embedding, but the embedding will be shoddy in comparison to one made with similar settings out of the collab. I know this from experience since I wasted 30 or something hrs training multiple embeddings locally trying to figure out why instead of looking at the bug reports first. The collab version works fine in comparison.

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  • textual_inversion

  • Rinongal and nicolai256 versions, the latter of which is also the one explained in Nerdy Rodent's youtube video https://www.youtube.com/watch?v=WsDykBTjo20, work but they also have an issue of lacking editability in comparison to one made by huggingface's collab which is followed up in a very long issue on Rinongal's Github. You can add accumulate_grad_batches: 4 to the end of the finetune files like shown in Nerdy Rodent's video at this time stamp to try to alleviate this issue, but the quality isn't as good as one made in the online collab.

  • Stable-textual-inversion_win

  • Rinongal and nicolai256 versions, the latter of which is also the one explained in Nerdy Rodent's youtube video https://www.youtube.com/watch?v=WsDykBTjo20, work but they also have an issue of lacking editability in comparison to one made by huggingface's collab which is followed up in a very long issue on Rinongal's Github. You can add accumulate_grad_batches: 4 to the end of the finetune files like shown in Nerdy Rodent's video at this time stamp to try to alleviate this issue, but the quality isn't as good as one made in the online collab.

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