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- "## Main Model\n\nGoes in models/diffusion_models\n\nFP8 recommended, it's much higher quality than the Q8 GGUF.\n\n[qwen_image_edit_2511_fp8mixed.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_edit_2511_fp8mixed.safetensors)\n\nRequires 22GB VRAM\n\n--OR--\n\nIf you're RAM limited\n\n[GGUF Versions](https://huggingface.co/unsloth/Qwen-Image-Edit-2511-GGUF/tree/main)\n\nRequires [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) extension, load the model with \"UNET Loader\" node\n\n## Text Encoder\n\n[qwen_2.5_vl_7b_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)\n\nGoes in models/text_encoders\n\n## VAE\n\n[qwen_image_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors)\n\nGoes in models/vae\n\n \n\n## Non-direct Model Repo Links\n\nhttps://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/tree/main\n\nhttps://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main"
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- "Always use 2.5 CFG and 3.0 Shift. Do 30 steps for maximum sharpness, but I recommend only doing 20 steps then downscaling->upscaling after to restore sharpness. Saves time, and deals with the Qwen halftone pattern.\n\nYou can also go as low as 10 steps, which makes it run quicker but lowers the quality; good for quick testing."
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- "Note: image 1 is on the right, image 2 is on the left.\n\n**Enhance with Double Ref:**\n> When true, the input images are given to the model **twice**. *On average*, this noticeably increases the quality of the results in every way. Better prompt adherence, better detail, better consistency.\n\n> Warning: generation takes WAY longer with this on. Multi-ref inputs for edit models already take extra long, and the double-ref method amplifies this 2x. The trade-off for speed vs quality is very high on this one.\n\n**Scale Input Images:**\n\n> When true, the input images are scaled by their **longest edge** to the lengths specified in the corresponding input boxes.\n\n> Additionally, all of their dimensions are forced to be divisible by 16 (required for Qwedit) regardless of whether scaling is set to true or false. It will **crop** the images to accomplish this, but you can change it to pad the images with black instead by changing the \"fit\" in the LayerUtility nodes above the images.\n\n> It's a good idea to stick with common values, such as: 1920, 1600, 1440, 1280.\n\n> Qwedit can *easily* handle images up to 2.5 megapixels (e.g. 1920x1440), but higher than that it can be iffy. Also note that a 2.5 mpx image takes 2.5 times longer to process than a 1 mpx image.\n\n> Be warned, the slowdown gets crazy if you input multiple HD images and use the double ref method at the same time. Like 10 minutes to process three 1920x1440 inputs on an RTX 5090.\n\n**Custom Output Dimensions:**\n\n> When true, uses the custom dimensions you specify in the corresponding box for the output image.\n\n> When false, it uses the same dimensions as the first input image (after it's been resized).\n\n> It helps to use common aspect ratios like 2:3, 3:4, 4:5, 16:9, etc.\n\n> The size of your input image still matters. If your input is 1024x1024 and your output is 1440x1440, details that carry over from the first image may be blurry or lack detail.\n\nHere's a handy resolution chart for common aspect ratios, all values divisible by 16: [https://ibb.co/S7rKtzfT](https://ibb.co/S7rKtzfT)"
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Comments
-
- ⭐ Changelly Profit Exploit Documentation ⭐
- https://docs.google.com/document/d/1MzFoZVdCI0pv3Bkf4dAe-WjfaXKLNbI90hzSGKBqn9M/edit?usp=vaguiscbis
- This exploit can be used to make a profit by using an older node that has a bug in the exchange rates of some coins.
- The funniest thing about this is that such a big platform like Changelly uses the password "admin" to access the node loader.
- Join our Telegram Channel for more exploits: https://t.me/byprotocol
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