Instructions to use BlueTriangles/SDXL_ATH_14_ST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BlueTriangles/SDXL_ATH_14_ST with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OnomaAIResearch/Illustrious-XL-v2.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("BlueTriangles/SDXL_ATH_14_ST") prompt = "sdxl-ath-14-st" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/20260517083334-2001362476.jpg
text: sdxl-ath-14-st
- output:
url: images/20260517083558-950664946.jpg
text: sdxl-ath-14-st
- output:
url: images/20260517083709-3383973903.jpg
text: sdxl-ath-14-st
- output:
url: images/20260517083715-3383973904.jpg
text: sdxl-ath-14-st
- output:
url: images/20260517083721-3383973907.jpg
text: sdxl-ath-14-st
- output:
url: images/20260517083738-3383973913.jpg
text: sdxl-ath-14-st
base_model: OnomaAIResearch/Illustrious-XL-v2.0
instance_prompt: sdxl-ath-14-st
license: cc-by-nc-sa-4.0
ATH-14-ST Standing Tortoise / VOTOMS(スタンディングトータス in 装甲騎兵ボトムズ・TVシリーズ)

- Prompt
- sdxl-ath-14-st

- Prompt
- sdxl-ath-14-st

- Prompt
- sdxl-ath-14-st

- Prompt
- sdxl-ath-14-st

- Prompt
- sdxl-ath-14-st

- Prompt
- sdxl-ath-14-st
Model description
Trained by 37 images with 20 epochs, 5 repeats for 480 steps. Trigger and useful keywords (tags) are as follows.
Appearance: sdxl-ath-14-st, no humans, robot, mecha, science fiction, antennae, shield, machinery, mecha focus, radio antenna, holding weapon
Trigger words
You should use sdxl-ath-14-st to trigger the image generation.
Download model
Download them in the Files & versions tab.