unprompted VS diffusers

I'm pleased to announce the release of Unprompted v10.0.0, the Swiss Army knife extension for A1111. This is a major update that brings a number of new features and improvements, including:

Unprompted: https://github.com/ThereforeGames/unprompted

you can get the same effect with unprompted zoom enhance feature. just paste this into the prompt field.

It's been a while since my last Unprompted post, so I wanted to share some of the new things you can do with this extension. 🙂

Also if you're curious, check out the Unprompted extension's implementation of img2pez for a1111 in img2img. Basic gist is that it uses machine learning to examine the image and tries to find tokens that would likely produce that image. I've found it to be pretty far off the mark most the time, but the terms it gives you can actually be quite useful.

There's a feature in unprompted that does this.

One thing to consider: there is an extension that will let you write some scripts as prompts, and it extends what you can do with wildcards. https://github.com/ThereforeGames/unprompted.git

Solution for 9.2.0: Use modified https://github.com/ThereforeGames/unprompted/issues/84 you posted. This made a stitch image in %TEMP% and had the modified image displayed in Auto1111 GUI. Only reason I am @ing is because if I had this issue on 9.2.0 I'm sure others are. I had to use FULL shortcode in wizard zoom enhance section; I had to use FULL shortcode in wizard zoom enhance section; [if batch_index=0][after][zoom_enhance show_original mask='face' replacement='[insert prompt]' mask_sort_method='left-to-right' upscale_method='Nearest Neighbor' downscale_method='Lanczos' blur_size=0.03 cfg_scale_min=3.0 denoising_max=0.65 mask_size_max=0.3 mask_method='clipseg' sharpen_amount=1.0 color_correct_method='none' color_correct_timing='pre' color_correct_strength=1.0 min_area=50.0 contour_padding=0.0 upscale_width=512.0 upscale_height=512.0 hires_size_max=1024.0][/after][/if]

It was a long time ago I used it but I think it takes some learning I would suggest reading the starter guide the short code relates to the extra detail but you need to learn how to write it I'm pretty sure there is a built in helper sorry I haven't used it extensively there must be a video guide on YouTube too there is for almost all of this ai stuff https://github.com/ThereforeGames/unprompted/blob/main/docs/GUIDE.md

And the updated extension here: https://github.com/ThereforeGames/unprompted

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