Modelpublic

imagepipeline/Juggernaut-XL-V9-RDPhoto2-Lightning_4S

sourceHugging Facecreativeml-openrail-mupdated 3y agoView on Hugging Face

2likes19downloads

Model Card

Juggernaut-XL-V9-RDPhoto2-Lightning_4S

This checkpoint model is uploaded on [imagepipeline.io](https://imagepipeline.io/)

Model details - Recommended Settings : Res: 832*1216 Sampler: DPM++ SDE Steps: 4-6 CFG: 1-2 Negative: Start with no negative, and add afterwards the Stuff you don´t wanna see in that image. HiRes: 4xNMKD-Siax200k with 2 Steps and 0.35 Denoise + 1.5 Upscale And a few keywords/tokens that I regularly use in training, which might help you achieve the optimal result from the version: Architecture Photography Wildlife Photography Car Photography Food Photography Interior Photography Landscape Photography Hyperdetailed Photography Cinematic Movie Still Mid Shot Photo Full Body Photo Skin Details

![Try this model](https://imagepipeline.io/models/Juggernaut-XL-V9-RDPhoto2-Lightning_4S?id=50643a0a-0f06-4159-affc-4c2e34552023/)

How to try this model ?

You can try using it locally or send an API call to test the output quality.

Get your API_KEY from imagepipeline.io. No payment required.

Coding in php javascript node etc ? Checkout our documentation

![documentation](https://docs.imagepipeline.io/docs/introduction)

python

import requests  
import json  
  
url =  "https://imagepipeline.io/sdxl/text2image/v1/run"  
  
payload = json.dumps({  
"model_id":  "50643a0a-0f06-4159-affc-4c2e34552023",  
"prompt":  "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K",  
"negative_prompt":  "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",  
"width":  "512",  
"height":  "512",  
"samples":  "1",  
"num_inference_steps":  "30",  
"safety_checker":  false,   
"guidance_scale":  7.5,  
"multi_lingual":  "no",  
"embeddings":  "", 
"lora_models": "", 
"lora_weights":  "" 
})  
  
headers =  {  
'Content-Type':  'application/json',
'API-Key': 'your_api_key'
}  
  
response = requests.request("POST", url, headers=headers, data=payload)  
  
print(response.text)

}

Get more ready to use MODELS like this for SD 1.5 and SDXL :

![All models](https://imagepipeline.io/models)

API Reference

Generate Image

http

  https://api.imagepipeline.io/sdxl/text2image/v1

Headers	Type	Description
`API-Key`	`str`	Get your `API_KEY` from imagepipeline.io
`Content-Type`	`str`	application/json - content type of the request body

Parameter	Type	Description
`model_id`	`str`	Your base model, find available lists in models page or upload your own
`prompt`	`str`	Text Prompt. Check our Prompt Guide for tips
`num_inference_steps`	`int [1-50]`	Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 30-50 (without LCM)
`guidance_scale`	`float [1-20]`	Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5
`lora_models`	`str, array`	Pass the model_id(s) of LoRA models that can be found in models page
`lora_weights`	`str, array`	Strength of the LoRA effect

license: creativeml-openrail-m tags:

—imagepipeline
—imagepipeline.io
—text-to-image
—ultra-realistic pinned: false pipeline_tag: text-to-image

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