detailed captioning only reduces your trained subject resemblance
detailed captioning only reduces your trained subject resemblance
Fbecause even if you caption the elements you dont want to be learnt, it still leaks info of what you want to be learnt
EOk, so no captions only caption tag in kohya? Should I use a high or low network dim for 50 images that are very consistent, I'm training a bag
Fi recommend use my config and dont change
Fyou can use folder name as caption
Fso like
F1_ohwx man
For have imagefile.txt files and write each one of them like ohwx man
Fboth works
EEx 24GB_GPU_Quality_Tier_1_22950MB_14.1_Second_IT_Trains_T5_and_T5_Attention.json ?
Fthat is config
Ffolder name means
F
Jdoes this matter? the outdated version
Fnope
Ffolder name doesnt matter we use latest version
UThank you 
The finetuned checkpoint is about 23gb, is there a way to reduce the size without losing the quality?
The finetuned checkpoint is about 23gb, is there a way to reduce the size without losing the quality?
Fyou can do lora
Fi dont remember if supporting save as fp8
UI tried lora but I like the outputs that im getting from finetuning. I see fewer overfits and more consistency in finetuned model.
Fye fine tune best
EI'm sonfused and have to ask again,
am I wrong in that you still can't train a full checkpoint below 80 gb vram? And finetuning means full checkpoint right?
am I wrong in that you still can't train a full checkpoint below 80 gb vram? And finetuning means full checkpoint right?
EThe lora turned out really bad. No shape from prodct at all, it only makes like a genral bag like it dosn't under geometry, or the shape is to complex
Ffull checkpoint can be trained as low as 6 gb vram
F6GB_GPU_5400MB_14.1_second_it_Tier_3_512px.json
Fthis is same as 48 gb config quality
F8GB_GPU_7500MB_20.5_second_it_Tier_1.json
ECould i use the 24 gb config for my rtx 4090?
F100%
Fpay attention to your empty vram
Fit uses 23 gb
Fyou can increase block swap count if you cant have 23 gb free due to other apps
EOk, could I do say 6 different colors of the same bag (same shape) in one checkpoint? I guess I would need captioning then.
Fi think you can train different colors of same bag
UHello,
I'm trying to run grid generator but I get this error, do you know why?
I'm familiar with comfyui but this is my first time trying swarmui
I'm trying to run grid generator but I get this error, do you know why?
I'm familiar with comfyui but this is my first time trying swarmui
U
Fhard to know without seeing all
Fyou can post debug logs here
UI was able to get it working. I pulled the latest code and it started working.
Uwhile generating images in a grid with multiple models, how does inpainting work? which image does it take as reference?
Fwhat kind of inpainting?
Fsegment?
Uyes, to make the face look more like the original character and to make it more clear
Fit inpaints every image
Fit generates
Fit is part of prompt
Uyes that I understand. While generating one image with one model it takes the first image that we generated as reference and inpaints the face right? but in grid generation, I didnt have a first image and I directly started generating images. My doubt is what reference would it take for inpainting if we dont have our first image generated?
Fit takes every generated image
Fand then inpaint face
UOh okay. I thought "1" in 1, 0.7, 0.5 meant take the first image as reference for inpainting the face <segment:yolo-face_yolov9c.pt-1,0.7,0.5//cid=11> that is why I was confused and wanted to know what would happen for the first image generation if we didn't have our first image generated.
F1 means first face in image
