RunDiffusion-FX-Photorealistic
This checkpoint model is uploaded on imagepipeline.io
Model details - How to use the model We set out to create a model that can accept small prompts yet generate amazing results. We've done that with RunDiffusion FX. Watch our guide on YouTube.
Small prompts work great!
(hyperrealism:1.2), BREAK fish swimming under the water BREAK (8K UHD:1.2), (photorealistic:1.2) Use a Negative!
e.g. Negative Prompt: plain background, boring, plain, standard, homogenous, uncreative, unattractive, opaque, grayscale, monochrome, distorted details, low details, grains, grainy, foggy, dark, blurry, portrait, oversaturated, low contrast, underexposed, overexposed, low-res, low quality, close-up, macro, surreal, multiple views, multiple angles Wide/Tall aspect ratios are awesome!
Resolutions like 480x832 832x480 work great then you can upscale.
Lower that CFG! You can use a CFG scale of 3.5 to 5 to get some softer photorealistic images
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
import requests
import json
url = "https://imagepipeline.io/sd/text2image/v1/run"
payload = json.dumps({
"model_id": "f46a1734-6a10-4348-ad29-b5068eed10cb",
"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/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 [email protected]
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