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Photo-Paint-Slider

creativeml-openrail-m

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Photo-Paint-Slider

This lora model is uploaded on imagepipeline.io

Model details - V2.0 After understanding the LECO training method, we will adjust the parameters and the learning rate in order to achieve better results with smaller files and fewer weights.

The available weights are from +2 to -2, and the recommended weights are from +2 to -1.0, with positive values providing animation tendency and negative values providing real tendency.

The performance of positive weight (animation) is better than negative weight (real).

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/sd/text2image/v1/run"  
  
payload = json.dumps({  
"model_id":  "sd1.5",  
"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": "8d995698-3aa1-4695-aca9-3d176401079b", 
"lora_weights":  "0.5" 
})  
  
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/sd/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/Photo-Paint-Slider