Small praise to the writers for having Our Vending Hero actually spend some time using new hot-food vending machine styles to please his chilly customers, and having Our DFC Genius Gal suddenly get nervous about undressing in front of him while Our Mighty Girlfriend waves away her concerns because it’s okay if it’s him.

The rest of the episode is a lengthy and pointless quest that accidentally succeeds because a new disposable annoying villain shows up and solves their problem with a whole lot of collateral damage. There’s nothing wrong with Our OP New Legal Loli, but they dropped a plot coupon when she appeared that added to the pile created by Our Not-Really-Evil Betrayers, and they’re going to have to cash them all in with breathless exposition soon, and I simply don’t care about that.

Verdict: lame with brief reminders of what made the first season good.

Qwen Image caption competition

Qwen Image follows prompts quite well, but as with all diffusion models, if a concept isn’t clearly tagged in the training data, then the model can’t easily produce it, and you have to assemble an incantation that resembles the desired concept.

Qwen Image does not grok spanking, and I simply could not get it to swing a hand, paddle, or bat at a buttock. But it wasn’t a total loss, since it turned out to have quite decent understanding of clothing and hair styles from the 1950s…

So, what captions spring to mind for this image? I’ll save my ideas for later. (click the image to see it at full size)

Qwen Image limitations

Around 90% of the “beautiful young women” I ask it to create are Statistically-Averaged White American Girls Who Could All Be Sisters. You have to push it away from the mean by adding descriptive words, which means I’ll be dusting off my wildcards to vary skin, hair, and eye color, ethnicity, figure, etc. Certain ethnic keywords produce significant changes, but the training data seems to be limited to only a handful of such tags.

There are a number of canned wildcard sets, and perhaps the most comprehensive are the “Billions of…” sets from DonMischo. As-is, they’re a bit too random, but the YAML has a decent structure, so I should be able to subset it and construct my own canned recipes for babe-making. Since SwarmUI doesn’t directly support YAML wildcard sets, I’ll use my wrapper script to generate large text files of prompts to use as standard wildcards.

That’s how I generated these, after filtering the file to remove the grannies and great-grannies:

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(all done with the lightning LoRA loaded, which is responsible for some of the reduced quality and tendency toward laser eyes, but not for the absurd combinations; that’s the wildcard set)

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