Instructions to use jayark/sammy-style-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jayark/sammy-style-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jayark/sammy-style-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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license: other
license_name: proprietary
tags:
- lora
- text-to-image
- style
- qwen-image-2512
library_name: diffusers
pipeline_tag: text-to-image
private: true
---
# Sammy Style LoRA
Style LoRA trained on **Qwen-Image-2512** to capture the Sammy children's book art style. Generates new characters, environments, and backgrounds in the style — not limited to any single character.
## Usage
- **Trigger word:** `sammy style`
- **Base model:** Qwen-Image-2512
- **Architecture:** LoRA (rank 16, alpha 4)
## Checkpoints
| File | Training Step | Notes |
|------|--------------|-------|
| `sammy-style-400.safetensors` | 400 | Earlier checkpoint |
| `sammy-style-600.safetensors` | 600 | Recommended — best quality/fidelity balance |
## Training Details
- ~50-70 training images (character images, backgrounds, synthetic fills)
- Natural language captions (not booru tags) — required by Qwen2.5-VL text encoder
- Captions describe content only; style is the learned residual
- 1500 total training steps; step 400-600 is the sweet spot before overfitting
|