--- language: - en thumbnail: "images/evaluate/striking a confident pose.../striking a confident pose_17_3.0.png" widget: - text: striking a confident pose output: url: images/striking a confident pose_17_3.0.png - text: striking a confident pose output: url: images/striking a confident pose_19_3.0.png - text: striking a confident pose output: url: images/striking a confident pose_20_3.0.png - text: striking a confident pose output: url: images/striking a confident pose_21_3.0.png - text: striking a confident pose output: url: images/striking a confident pose_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: "striking a confident pose" base_model: "stabilityai/stable-diffusion-xl-base-1.0" --- # ntcai.xyz slider - striking a confident pose (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: ``` striking a confident pose ``` ## 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.striking-a-confident-pose', weight_name='striking a confident pose.safetensors', adapter_name="striking a confident pose") # Activate the LoRA pipe.set_adapters(["striking a confident pose"], adapter_weights=[2.0]) prompt = "medieval rich kingpin sitting in a tavern, striking a confident pose" 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