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Support Lumina-image-2.0 #1927

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Support Lumina-image-2.0 #1927

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sdbds
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@sdbds sdbds commented Feb 12, 2025

Still in preparation.

After checking their sampler using flux and vae, the textencoder part uses google's gemma2

@kohya-ss CC

@sdbds sdbds marked this pull request as draft February 12, 2025 08:32
@sdbds sdbds mentioned this pull request Feb 12, 2025
@rockerBOO
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I got this setup locally, I know it's not ready for anything but I want to get it working. Let me know if you want to work together on this. I can help with some of the model loading parts which is where I got stuck with after poking at it. If you are progressed past this, I can help wherever else or just testing.

Thanks.

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sdbds commented Feb 15, 2025

I got this setup locally, I know it's not ready for anything but I want to get it working. Let me know if you want to work together on this. I can help with some of the model loading parts which is where I got stuck with after poking at it. If you are progressed past this, I can help wherever else or just testing.

Thanks.

Thank you, the framework is basically set up at the moment, but there is still some room for improvement in the caching strategy.

I think I can discuss with @kohya-ss whether to continue using the previous method.

#1924 (comment)

@sdbds sdbds marked this pull request as ready for review February 15, 2025 09:12
@envy-ai
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envy-ai commented Feb 15, 2025

Thank you, the framework is basically set up at the moment, but there is still some room for improvement in the caching strategy.

Does that mean I can download your fork and test it now?

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It's still not quite working but I'm working through some issues at the moment. Mostly with model loading but will see what else is needed after that. It is fairly barebones so wouldn't expect it to be in working state just yet.

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sdbds commented Feb 17, 2025

After multiple updates, the project can now run under limited conditions:

  1. Flash_attn on Windows will cause NAN, so it must be run in a Linux environment.
    Later consideration will be given to transforming it into SDP or xformers-driven
  2. The POS ID calculation for token sequences is not padded to the max length, which leads to the necessity of batchsize = 1

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3 participants