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Omni-Image-Editor

like 2.08k

Running on CPU Upgrade

how can i download this model and deploy on my server?

We have open-sourced the model architecture and sampling code.
Due to training data privacy constraints, we are required to apply certain limitations to the model weights prior to release.
Our team is actively evaluating possible approaches to make this happen.

What's the key to doubling the storage space, or where can I find it?

how can i download this model and deploy on my server?

short answer they won't. ...

how can i download this model and deploy on my server?

short answer they won't. ...

yea it sucks

"Processing failed: task processing failed: missing task_id"

Got notification like that, what happen? What am i supposed to do? How to fix that? Any solution? Help

how can i download this model and deploy on my server?

Here is the Comfyui workflow they use, simply copy/download it and put it in Comfyui. Not sure why they were so hell bent on keeping this private, claiming they spend so much money on RnD and shit when they just use trained models from someone else, well probably so people go their website and buy a subscription model but even then why not just tell what you use for the people who have the computers to run it themselves lmao, there are still plenty of people who would have payed money because their pc's just arent powerfull enough

Workflow (copy/dragNdrop into comfyui):
https://pastebin.com/qzrhqENx

and here is the model they use:
https://huggingface.co/Phr00t/Qwen-Image-Edit-Rapid-AIO/tree/main/v19

so much about them "training the model themselves"

btw you can check yourself by just putting the output images in a hexeditor or comfyui itself:
{"1": {"inputs": {"ckpt_name": "v19/Qwen-Rapid-AIO-NSFW-v19.safetensors"}, "class_type": "CheckpointLoaderSimple", "_meta": {"title": "REDACTED"}}, "2": {"inputs": {"seed": REDACTED, "steps": 4, "cfg": 1.0, "sampler_name": "lcm", "scheduler": "beta", "denoise": 1.0, "model": ["1", 0], "positive": ["3", 0], "negative": ["4", 0], "latent_image": ["9", 0]}, "class_type": "KSampler", "_meta": {"title": "REDACTED"}}, "3": {"inputs": {"prompt": "REDACTED", "target_size": 896, "clip": ["1", 1], "vae": ["1", 2], "image1": ["7", 0]}, "class_type": "TextEncodeQwenImageEditPlus", "_meta": {"title": "TextEncodeQwenImageEditPlus Input Prompt"}}, "4": {"inputs": {"prompt": "", "target_size": 800, "clip": ["1", 1], "vae": ["1", 2]}, "class_type": "TextEncodeQwenImageEditPlus", "_meta": {"title": "TextEncodeQwenImageEditPlus Negative (leave blank)"}}, "5": {"inputs": {"samples": ["2", 0], "vae": ["1", 2]}, "class_type": "VAEDecode", "_meta": {"title": "REDACTED"}}, "6": {"inputs": {"images": ["5", 0]}, "class_type": "PreviewImage", "_meta": {"title": "REDACTED"}}, "7": {"inputs": {"image": "REDACTED"}, "class_type": "LoadImage", "_meta": {"title": "Optional Input Image"}, "is_changed": ["REDACTED"]}, "9": {"inputs": {"width": 984, "height": 648, "batch_size": 1}, "class_type": "EmptyLatentImage", "_meta": {"title": "Final Image Size"}}}