sd-parseq VS diffusers

This is how it was done https://github.com/rewbs/sd-parseq/discussions/106

rewbs/sd-parseq (github.com)

sd-parseq for parameter control / keyframing.

I need to modify Parseq to add a way for you to be able to specify absolute values and then render deltas/slopes for use in loopback-based animations. Otherwise it's too hard to say e.g. "I want a 180 degree rotation over 16 beats": you have to figure out what increments will add up to 180 manually.

Cool! Correct me if I'm wrong, but isn't that kind of animation essentially loopback with incremental transforms on each frame before feeding back into SD? If so, that's why I'm so excited about the colour improvements too (I'm the author of sd-parseq, a tool for SD animations: https://github.com/rewbs/sd-parseq)! :)

As described in this post, I've been working on a script for automatic1111 UI with its own separate companion UI for "sequencing" parameter changes over multiple generations, resulting in interesting videos that you can control precisely. This video gives a quick & dirty demo to give you a better idea of what it does. The output described in that video looks like this. If you're feeling adventurous you can check out the param flows directly in the parseq UI here (NB: only tested in Chrome so far, uses massive URLs which some browsers don't like). The code is here: https://github.com/rewbs/sd-parseq

I've been playing with the idea of a custom script + companion UI to give fine grained control over various parameters when generating videos. It's still very rough but I think it's just about ready to share: https://github.com/rewbs/sd-parseq

ShivamShrirao's Diffusers Pretrained diffusion models across multiple modalities.

Like the title say I'm trying to fine-tune a model to match a style of a popular manhwa. I'm using the ShivamShrirao Google Colab to accomplish this.

I am running the DreamBooth_Stable_Diffusion.ipynb notebook from ShivamShrirao locally on my machine. Let's say I have trained for 500 iterations and it hasn't converged yet. How do I make it resume training from that iteration so it can do another 500?

My understanding, based on messages from an (alleged) representative of colabs, is that the webui is the problem, not SD itself. This also seems to be the consensus in the comments section of other posts. I have not yet seen a link to colab based webui alternatives so here is something I found from a tutorial. I am certain that there are better alternatives. Anyone have a better idea? This will still probably be useful to other people like me who are just messing around.

I'm running ShivamShrirao's fork of diffusers; ran into a fp16 issue and had to patch in a fix from the main branch ( #1567 ).

I am running Shivam Stable Diffusion Jupyter notebook: diffusers/DreamBooth_Stable_Diffusion.ipynb at main · ShivamShrirao/diffusers · GitHub.

Are you using this one? https://github.com/S