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imagepipeline/
Animagine-XL-v3

Name: Animagine-XL-v3
Availability: InStock

creativeml-openrail-m

autotrain_compatible

endpoints_compatible

StableDiffusionXLPipeline

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Animagine-XL-v3

This checkpoint model is uploaded on imagepipeline.io

Model details - Recommended settings: To guide the model towards generating high-aesthetic images, use negative prompts like: nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist name. For higher quality outcomes, prepend prompts with: masterpiece, best quality. However, be careful to use masterpiece, best quality because many high-scored datasets are NSFW. It’s better to add nsfw, rating: sensitive to the negative prompt and rating: general to the positive prompt. it’s recommended to use a lower classifier-free guidance (CFG Scale) of around 5-7, sampling steps below 30, and to use Euler Ancestral (Euler a) as a sampler.

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

python

import requests  
import json  
  
url =  "https://imagepipeline.io/sdxl/text2image/v1/run"  
  
payload = json.dumps({  
"model_id":  "bd1a6e69-8df3-4735-9817-991d190c3cb6",  
"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 :

API Reference

Generate Image

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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imagepipeline/Animagine-XL-v3