README.md

---
language: en
tags:
- stable-diffusion
- sdxl
- lora
- image-generation
- style-transfer
- sketch
license: creativeml-openrail-m
---

# Model Card for SDXL Sketch-Style LoRA

## Model Details

### Model Description

This model is a **LoRA fine-tuning module** for **SDXL-based anime and art-style image generation models**.  
It transforms polished renders into **sketch-like / draft illustration** variants by emphasizing linework, rough shading, and reduced color saturation while preserving composition and subject structure.

- **Developed by:** WorthyHuman1  
- **Model type:** LoRA (Low-Rank Adaptation) for SDXL  
- **License:** CreativeML Open RAIL-M  
- **Finetuned from model:** SDXL 1.0–compatible anime/art checkpoints


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## Uses

### Direct Use

Load this LoRA into any **SDXL-compatible pipeline** that supports LoRA weights to produce sketch-style outputs from text prompts.

Common use cases:
- Generating draft/concept-art sketches
- Exploring stylistic variations
- Educational demonstrations of style fine-tuning

### Downstream Use

Can be combined with:
- Other LoRAs (character, pose, lighting)
- Custom SDXL pipelines and workflows

### Out-of-Scope Use

- Photorealistic image generation
- High-fidelity full-color illustration
- Deceptive or misleading content generation

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## Bias, Risks, and Limitations

- Output quality depends on base model and prompt phrasing.  
- Strong LoRA weights may oversimplify textures or reduce color fidelity.  
- Style reflects patterns in the training data and may not generalize uniformly across all art styles.

### Recommendations

- Experiment with LoRA strengths between `0.6` and `1.0`.  
- Use sketch-related keywords: `sketch`, `rough lineart`, `pencil drawing`, `unfinished illustration`.  
- Combine with an appropriate SDXL base model for best results.

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## How to Get Started

**Suggested prompt keywords:**
sketch_style, rough lineart, pencil drawing, unfinished illustration

**Recommended LoRA strength:** `0.6 – 1.0`

Compatible with common SDXL tools (Diffusers, AUTOMATIC1111, ComfyUI, etc.).

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## Training Details

### Training Data

Trained on a curated dataset of sketch-style and draft illustration images, filtered to emphasize line-based structure and reduced rendering polish. Training focused on style transformation rather than subject memorization.

### Training Procedure

Parameter-efficient fine-tuning using LoRA techniques on SDXL-compatible layers.

#### Training Hyperparameters

- **Precision / regime:** fp16 mixed precision

#### Compute

- **Hardware:** NVIDIA GeForce RTX 4050  
- **Approximate training time:** 16 hours

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## Evaluation

### Testing Data, Factors & Metrics

Evaluation performed qualitatively across multiple SDXL base models and diverse prompts covering characters, portraits, and scenes. Assessment prioritized visual coherence, stylistic consistency, and prompt adherence via side-by-side comparisons.

### Results

Produces consistent sketch-like outputs while preserving core composition across a variety of prompts when paired with suitable base models.

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## Environmental Impact

- **Hardware:** NVIDIA GeForce RTX 4050  
- **Hours used:** ~16 hours  
- **Compute region:** local / on-prem

(Estimate only)

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## Technical Specifications

### Model Architecture and Objective

- Architecture: SDXL LoRA  
- Objective: Style adaptation toward sketch/draft aesthetics

### Software

- SDXL-compatible inference/training tools  
- LoRA training framework (PyTorch-based)

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## Model Card Authors

- WorthyHuman1

## Model Card Contact

- Hugging Face: `@WorthyHuman1`