--- language: - en thumbnail: "images/evaluate/long exposure photography.../long exposure photography_17_3.0.png" widget: - text: long exposure photography output: url: images/long exposure photography_17_3.0.png - text: long exposure photography output: url: images/long exposure photography_19_3.0.png - text: long exposure photography output: url: images/long exposure photography_20_3.0.png - text: long exposure photography output: url: images/long exposure photography_21_3.0.png - text: long exposure photography output: url: images/long exposure photography_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: "long exposure photography" base_model: "stabilityai/stable-diffusion-xl-base-1.0" --- # ntcai.xyz slider - long exposure photography (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: ``` long exposure photography ``` ## 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.long-exposure-photography', weight_name='long exposure photography.safetensors', adapter_name="long exposure photography") # Activate the LoRA pipe.set_adapters(["long exposure photography"], adapter_weights=[2.0]) prompt = "medieval rich kingpin sitting in a tavern, long exposure photography" 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 950+ 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