Background Removal
🌘
2.68k
Remove background from images
Sergio K PRO
Sergidev
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LLM & Deep Learning
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Next level Realism with Qwen Image is now possible after new realism LoRA workflow - Top images are new realism workflow - Bottom ones are older default - Full tutorial published - 4+4 Steps only
Tutorial of realism : https://youtu.be/XWzZ2wnzNuQ
Tutorial of training : https://youtu.be/DPX3eBTuO_Y
This is a full comprehensive step-by-step tutorial for how to train Qwen Image models. This tutorial covers how to do LoRA training and full Fine-Tuning / DreamBooth training on Qwen Image models. It covers both the Qwen Image base model and the Qwen Image Edit Plus 2509 model. This tutorial is the product of 21 days of full R&D, costing over $800 in cloud services to find the best configurations for training. Furthermore, we have developed an amazing, ultra-easy-to-use Gradio app to use the legendary Kohya Musubi Tuner trainer with ease. You will be able to train locally on your Windows computer with GPUs with as little as 6 GB of VRAM for both LoRA and Fine-Tuning.
Tutorial of realism : https://youtu.be/XWzZ2wnzNuQ
Tutorial of training : https://youtu.be/DPX3eBTuO_Y
This is a full comprehensive step-by-step tutorial for how to train Qwen Image models. This tutorial covers how to do LoRA training and full Fine-Tuning / DreamBooth training on Qwen Image models. It covers both the Qwen Image base model and the Qwen Image Edit Plus 2509 model. This tutorial is the product of 21 days of full R&D, costing over $800 in cloud services to find the best configurations for training. Furthermore, we have developed an amazing, ultra-easy-to-use Gradio app to use the legendary Kohya Musubi Tuner trainer with ease. You will be able to train locally on your Windows computer with GPUs with as little as 6 GB of VRAM for both LoRA and Fine-Tuning.
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C/ua Cloud Containers - Docker for Computer-Use Agents. Zero local setup. Same Computer and Agent interfaces. Scale 1-100 agents instantly.
Github : https://github.com/trycua/cua
Website : https://www.trycua.com
Github : https://github.com/trycua/cua
Website : https://www.trycua.com
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