Thatdoes look a bit like a circuit board...

TODO for when image generation works

I can't figure out what I'm doing wrong, I think it is supposed to be working just like Flux1, but with different PE indices and Qwen Text Encoder.... Maybe I'm missing an important detail but I can't find it.

I tried using my SplitAttention thing on a Flux model converted to diffusers format, and

I guess I found what is not working. I will try converting LongCat to Flux format and see if it works.

I think I got it?

With the padding fixed, but with diffusers format:

With the character-level tokenization trick:

Might need testing to make sure the current implementation supports languages that don't use the latin alphabet. Also for now it's applied to text wrapped in single quotes ( ') only.

Oh no, why are there so many conflicts now?

Using' as a quote delimiter was a bad idea because it's the same symbol used for apostrophes. I will change it to detect" instead

Somehow not fully working yet, but it's definitely able to see it's supposed to be a cat holding a sign, maybe because of the vision model
sd.exe --diffusion-model ..\ComfyUI\models\unet\longcat_edit_bfl_format-Q8_0.gguf --vae ..\ComfyUI\models\vae\flux\ae.safetensors --cfg-scale 4.5 --sampling-method euler -v --offload-to-cpu --preview proj --steps 50 --vae-tile-size 128 --qwen2vl ..\ComfyUI\models\clip\Qwen2.5-VL-7B-Instruct.Q4_K_M.gguf --color --seed 0 -r .\assets\flux\flux1-dev-q8_0.png --llm_vision ..\ComfyUI\models\clip_vision\Qwen2.5-VL-7B-Instruct.mmproj-f16.gguf -p "Change the text to say \"I'm a long one\""

ref	out

(Also I made the change so it now needs double quotes around literal text)

Somehow couldn't get it to remove the original text, but there it goes

May I ask which comfyui node is used to load this GGUF model?

Now supports UTF-8 encoding properly for the quoted text. (also quote characters are no longer excluded from the prompt after being parsed, seems to help a bit, especially with longer text.)

May I ask which comfyui node is used to load this GGUF model?

@Rocky-Lee-001 I don't think LongCat-Image is natively supported by ComfyUI yet. You could givehttps://github.com/sooxt98/comfyui_longcat_image a try, maybe it works well with the GGUF node for comfyUI?

I’m not sure whether I did something wrong on my end, but I got a strange image.

.\bin\Release\sd-cli.exe --diffusion-model  ..\models\longcat_bfl_format-Q4_K_M.gguf --vae ..\..\ComfyUI\models\vae\ae.sft  --llm ..\..\ComfyUI\models\text_encoders\Qwen2.5-VL-7B-Instruct-Q8_0.gguf -p 'a lovely cat' --cfg-scale 5.0 -v --offload-to-cpu --diffusion-fa

@leejet that's strange. I can reproduce it with the same prompt though (even with Q8_0 model), but I haven't gotten anything like this in my earlier testing. Maybe There's a linear layer that could use scaling?

Does not seem related to seed.

It's a combination of short prompts + low resolution that seems to cause it.

I think there are still some differences between the implementation in this PR and the official pipeline—for example, the way token padding is handled and whether masks are used. I suspect these differences might be what caused the strange blocky artifacts in the generated images. I tried to fix it, but didn’t succeed; now it’s producing completely black images.

https://github.com/leejet/stable-diffusion.cpp/tree/longcat-fix

I've tried this code and found out that short prompts lead to such a blocky modern-art generations, while long descriptive prompts produce higher quality results

For example~/projects/longcat.cpp/build/bin/sd --diffusion-model ~/Drive/AI/ComfyUI/models/unet/longcat_bfl_format-Q4_K_M.gguf --diffusion-fa --vae ~/Drive/AI/ComfyUI/models/vae/ae.sft --sampling-method euler --cfg-scale 3.0 --steps 20 --llm ~/Drive/AI/ComfyUI/models/text_encoders/Qwen2.5-VL-7B-Instruct-Q3_K_M.gguf --color -W 512 -H 512 --seed 128 -o output_$(date +%Y-%m-%d_%H-%M-%S).png --vae-tiling -p "Orange cat":

Repeating "Orange Cat" several times:

~/projects/longcat.cpp/build/bin/sd --diffusion-model ~/Drive/AI/ComfyUI/models/unet/longcat_bfl_format-Q4_K_M.gguf --diffusion-fa --vae ~/Drive/AI/ComfyUI/models/vae/ae.sft --sampling-method euler --cfg-scale 3.0 --steps 20 --llm ~/Drive/AI/ComfyUI/models/text_encoders/Qwen2.5-VL-7B-Instruct-Q3_K_M.gguf --color -W 512 -H 512 --seed 128 -o output_$(date +%Y-%m-%d_%H-%M-%S).png --vae-tiling -p "This is a portrait photograph of an Orange Cat sitting on the table by the window. We can see the room interior, fancy 50s style Art-Deco ornaments on the wallpaper. The weather outside is fine, the sun is shining. Wintertime snow on the ground, people playing with snowballs. The cat is large and shaped like a sphere. Whiskers are long and fangs are sharp. Phone snapshot, photograph."

Increasing step count would reduce artifacts even more. However face seems bit blocky anyway, not sure if it would be true for original workflow, can not run non-gguf model on my GPU. Also increasing resolution would not help with those artifacts.

Hope my observations might be helpful

P.S. I've also checked out@leejetlongcat-fix branch. It generated black images indeed, until I added--clip-on-cpu, then i could get image with just "Orange Cat" prompt!