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Quiho/Cranberry_XL_Cranberry_V4_checkpoint
Cranberry_XL_Cranberry_V4_checkpoint is a machine learning model from Quiho. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusers.
Downloads · 30 days
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8% of all-time downloads
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From the Hugging Face model README
V4 NEW VERSION OUT! with magic and a lot of time Cranberry is now SDXL Based. I took Cranberry V2 and force fed it to SDXL models until a decent base appeared that i trained over a new data set of 10 000 images. trained to fit an anime aesthetic with a lot of prompting freedom, it can generate great anthro/feral/human results VAE IS NOT BAKED IN PLEASE USE SDXL VAE Cranberry_4: Second version, trained on a larger dataset of about 10 000 images with a lot of new concepts and artists thanks to SDXL
Trained it with custom captions to still perform good on minimalistic prompts (You really can have a wide range of results for a single prompt) Positive: Same as sdxl, simple as "amazing quality, best quality" Negative: lowres, bad quality and worst quality are nice none but (monochrome, greyscale) are sometimes good as the model tend to generate monochrome images, you can also put (cartoon, toon) if you want to have a real anime look
PS: also for some reasons, High.res fix of 1.5 works better than 2 so use it :)
OLD VERSIONS PonyXl trained to fit an anime aesthetic with a lot of prompting freedom, it can generate great anthro/feral/human results VAE IS NOT BAKED IN PLEASE USE PONY VAE Cranberry_2: Second version, trained on a larger dataset of about 4000 images for about 100 epochs per images Cranberry_1: First version, trained on a small dataset of about 2000 images for about 100 epochs per images
Trained it with custom captions to still perform good on minimalistic prompts (You really can have a wide range of results for a single prompt) Positive: Same as pony, no need for source:anime, but place them at THE END of your prompt to have better results ( score_9, score_8_up, score_7_up, score_6_up, score_5_up, score_4_up) BUT (score_9) only gives good result too AND (score_6_up, score_5_up, score_4_up) only act as a "good" version of the raw without positives result so try to use it too Negative: none but (monochrome, greyscale) are sometimes good as the model ten...
Original model by: N_Endo Civitai: Link