qwen-ed-skin

About

What qwen-ed-skin is

Qwen-Edit-Skin Model description EDIT- Version 1.1 uploaded with better convergence, less artifacts and more room in strengths to play with. See "Full comparision" examples in the image folder here. Finetuned LoRA for Enhanced Skin Realism in Qwen-Image-Edit-2509 You can find a deeper dive article into my approach for this LORA here on LinkedIn: This repository contains a finetuned Low-Rank Adaptation (LoRA) model designed to enhance the realism and detail of human skin in images. The LoRA has been trained on top of the powerful Qwen/Qwen-Image-Edit-2509 model, leveraging its advanced image editing capabilities to focus specifically on generating more natural and detailed skin textures. This model was trained for 5000 steps on a local RTX 5090 using the AI-Toolkit. The resulting LoRA is ideal for photographers, digital artists, and anyone looking to improve the quality of human subjects in their generated or edited images. Model Description The qwen-edit-skin LoRA is a specialized finetuning of the Qwen/Qwen-Image-Edit-2509 base model. The base model is a versatile image editor with strong capabilities in multi-image editing and maintaining single-image consistency, particularly in preserving personal identity. This LoRA builds upon that foundation to specifically address the nuances of human skin, adding detail and realism that may not be present in the original generations. The training was conducted using this fork of AI ToolKit, a comprehensive suite for finetuning diffusion models. The process for curating the dataset involved reverse modification of subject skin details as follows: Taking real images of versatile subject portraits with skin exposed Captioning each of these as our "Target" (THE AFTER) images for the final outcome expected in a standard Qwen Edit workflow Editing the image in Photoshop to add more gaussian blur and smoother skin tones, to make the skin texture, tone and pores less visible These became our "Control" (The BEFORE) images for Qwen Edit training. Training Details The model was finetuned with the following key parameters, which can be found in the accompanying config.yaml file: Hardware: - GPU: NVIDIA

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How image models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys qwen-ed-skin for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen-ed-skin below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen-ed-skin","prompt":"a red bicycle","size":"1024x1024"}'

Details

Languages, data & research

Licence

Open weights

Sources

Weights & code

Explore

More image models