---
language:
- en
thumbnail: "images/evaluate/in a hot air balloon race.../in a hot air balloon race_17_3.0.png"
widget:
- text: in a hot air balloon race
output:
url: images/in a hot air balloon race_17_3.0.png
- text: in a hot air balloon race
output:
url: images/in a hot air balloon race_19_3.0.png
- text: in a hot air balloon race
output:
url: images/in a hot air balloon race_20_3.0.png
- text: in a hot air balloon race
output:
url: images/in a hot air balloon race_21_3.0.png
- text: in a hot air balloon race
output:
url: images/in a hot air balloon race_22_3.0.png
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
license: "mit"
inference: false
instance_prompt: "in a hot air balloon race"
base_model: "stabilityai/stable-diffusion-xl-base-1.0"
---
# ntcai.xyz slider - in a hot air balloon race (SDXL LoRA)
| Strength: -3 | Strength: 0 | Strength: 3 |
| --- | --- | --- |
| | | |
| | | |
| | | |
## Download
Weights for this model are available in Safetensors format.
## Trigger words
You can apply this LoRA with trigger words for additional effect:
```
in a hot air balloon race
```
## Use in diffusers
```python
from diffusers import StableDiffusionXLPipeline
from diffusers import EulerAncestralDiscreteScheduler
import torch
pipe = StableDiffusionXLPipeline.from_single_file("https://huggingface.co/martyn/sdxl-turbo-mario-merge-top-rated/blob/main/topRatedTurboxlLCM_v10.safetensors")
pipe.to("cuda")
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
# Load the LoRA
pipe.load_lora_weights('ntc-ai/SDXL-LoRA-slider.in-a-hot-air-balloon-race', weight_name='in a hot air balloon race.safetensors', adapter_name="in a hot air balloon race")
# Activate the LoRA
pipe.set_adapters(["in a hot air balloon race"], adapter_weights=[2.0])
prompt = "medieval rich kingpin sitting in a tavern, in a hot air balloon race"
negative_prompt = "nsfw"
width = 512
height = 512
num_inference_steps = 10
guidance_scale = 2
image = pipe(prompt, negative_prompt=negative_prompt, width=width, height=height, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
image.save('result.png')
```
## Support the Patreon
If you like this model please consider [joining our Patreon](https://www.patreon.com/NTCAI).
By joining our Patreon, you'll gain access to an ever-growing library of over 1140+ unique and diverse LoRAs, covering a wide range of styles and genres. You'll also receive early access to new models and updates, exclusive behind-the-scenes content, and the powerful LoRA slider creator, allowing you to craft your own custom LoRAs and experiment with endless possibilities.
Your support on Patreon will allow us to continue developing and refining new models.
## Other resources
- [CivitAI](https://civitai.com/user/ntc) - Follow ntc on Civit for even more LoRAs
- [ntcai.xyz](https://ntcai.xyz) - See ntcai.xyz to find more articles and LoRAs