Hugging Face's logo

imagepipeline
/
Deep-Negative-V1

Text-to-Image
imagepipeline
imagepipeline.io
ultra-realistic
Model card Files Community
Deep-Negative-V1 / README.md
image-pipeline's picture
image-pipeline
Upload README.md with huggingface_hub
1c7188f
preview code
|
raw
history blame
4.67 kB
metadata
license: creativeml-openrail-m
tags:
  - imagepipeline
  - imagepipeline.io
  - text-to-image
  - ultra-realistic
pinned: false
pipeline_tag: text-to-image

Deep-Negative-V1

Generated by Image Pipeline

This embedding model is uploaded on imagepipeline.io

Model details - Pass trigger words in negative prompt

Try this model

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 

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":  "b95f1585-65b6-4ba0-b891-a3e24f49c055", 
"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

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

Feedback

If you have any feedback, please reach out to us at hello@imagepipeline.io

🔗 Visit Website

portfolio

If you are the original author of this model, please click here to add credits