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Joined 8 months ago
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Cake day: October 6th, 2024

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  • From what I can gather, the dev doesn’t like interacting very much. This is something that they do in their spare time as a fulltime dev. They created the perchance platform first and foremost as a way for people to learn code and web development. The AI was always a side feature.

    There has also been a lot of grumbling in the perchance community (both here, in the comments of various generators, on reddit, and on the Discord server) about the quality of the previous image generator (plus plenty of feedback via the feedback tool, I’m sure), so it isn’t really a surprise that he/she finally made the switch to a new model after stating that they planned to in more than one post here in this forum.

    In addition, I didn’t see anyone (before the change in model) praising the old one… only complaints about the quality, resolution, coherence, etc. Now that a new model is in place, suddenly many people have lots good things to say about the old one.

    Bottom line, this is a completely free, uncensored, private, and unlimited service that the dev was kind enough to gift to us. I’m certainly not going to complain when I don’t even know what the final outcome is going to be yet.


  • You know, a lot of the trouble could have been avoided if people would simply read the notes about the change and have a little patience. It says right in there that the model is still training, so it literally doesn’t have all the data needed to make images similar to the old one, yet. It’s starting at base settings and parameters, so expect a lot of strange variance and “sameness”.

    For those wondering why we can’t have the old one as an option still, the answer is simple: memory (RAM). These image models don’t spin up instantly, so they need to remain loaded in memory in order to field requests. To have the old one running at the same time would mean effectively doubling the resources required when the dev is already running on a shoestring budget supported entirely by ad revenue. It’s either one running or the other. In order to train the new model, it must be running, which means the old one can’t run at the same time.