Stable Cascade Prompt Following Is Amazing — This Model Has Huge Potential — High Resolutions Uses Lesser VRAM & Still Very Fast — Check Comments For
Furkan G?zükara
PhD. Computer Engineer. Produces Content For FLUX, LoRA, Fine Tuning, Stable Diffusion, SDXL, Training, DreamBooth Training, Deep Fake, Voice Cloning, Text To Speech, Text To Image, Text To Video, Generative AI, LLMs
You can download our scripts here : https://www.patreon.com/posts/98410661
Stability AI recently released Stable Cascade. You can read here : https://github.com/Stability-AI/StableCascade
I have developed an amazing 1 click installer and Gradio app for this newest amazing model.
This model can be considered as next level of Stable Diffusion.
The gradio APP I developed supports low VRAM and works great on even 8 GB GPUs
Saves every generated image automatically in outputs folder and many a lot of improvements
Kaggle not working right now due to FP16 bug and I have reported it to be fixed. Hopefully after that notebook will work great
Batch size 4, 1536x1280 resolution it / s is 1.7 on RTX 4090
Batch size 1, 1024x1024 resolution it / s is 12.14 (encoder) / 10.6 (decoder) on RTX 4090
So 1 image takes like 4 seconds on RTX 4090 for 1024x1024
zCHG - WeCharg - StealthMachines - Love Letter Media - Josef K Media - trisandcats.com
1 年“I been to the desert on a horse with no name…”
Generative AI Prompt Curator | Pharmacist | Connector of people across technology, healthcare and finance
1 年This is amazing.
AI & Machine Learning Developer @ AFRY
1 年Also changing "Decoder Guidance Scale (CFG)" above 1 seem to generate this error: Traceback (most recent call last): ?File "Q:\StableCascade\venv\lib\site-packages\gradio\queueing.py", line 495, in call_prediction ??output = await route_utils.call_process_api( ........................ ?File "Q:\StableCascade\venv\lib\site-packages\diffusers\pipelines\stable_cascade\modeling_stable_cascade_common.py", line 304, in forward ??x = x + self.effnet_mapper( RuntimeError: The size of tensor a (2) must match the size of tensor b (4) at non-singleton dimension 0 Also values 0-1 does no diffrence for the generation
AI & Machine Learning Developer @ AFRY
1 年Changing "Prior Inference Steps" does nothing. It still runs 29 prior inference steps and there is no difference in speed or the look of the image. Some code missing? :)