Text-to-Image
Diffusers
English
stable-diffusion-xl
lora
template:sd-lora
template:sdxl-lora
sdxl-sliders
ntcai.xyz-sliders
concept
Instructions to use ntc-ai/SDXL-LoRA-slider.the-feeling-of-achieving-max-power with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ntc-ai/SDXL-LoRA-slider.the-feeling-of-achieving-max-power with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ntc-ai/SDXL-LoRA-slider.the-feeling-of-achieving-max-power") prompt = "the feeling of achieving max power" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
ntcai.xyz slider - the feeling of achieving max power (SDXL LoRA)
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Download
Weights for this model are available in Safetensors format.
Trigger words
You can apply this LoRA with trigger words for additional effect:
the feeling of achieving max power
Use in diffusers
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.the-feeling-of-achieving-max-power', weight_name='the feeling of achieving max power.safetensors', adapter_name="the feeling of achieving max power")
# Activate the LoRA
pipe.set_adapters(["the feeling of achieving max power"], adapter_weights=[2.0])
prompt = "medieval rich kingpin sitting in a tavern, the feeling of achieving max power"
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')
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Model tree for ntc-ai/SDXL-LoRA-slider.the-feeling-of-achieving-max-power
Base model
stabilityai/stable-diffusion-xl-base-1.0







