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ModelsLab/AbsoluteReality

AbsoluteReality
Text to Image Community ModelFree for Premium UsersLLMs.txt
Suggestions Use between 4.5 and 10 CFG Scale and between 25 and 30 Steps with DPM++ SDE Karras. Worse samplers might need more steps. To reproduce my results you might have to change these settings: Set "Do not make DPM++ SDE deterministic across different batch sizes." Set the ETA Noise Seed Delta (ENSD) to 31337 Set CLIP Skip to 2 DISABLE face restore. It's terrible, never use it Use simple prompts. Complex prompts might make less realistic pictures because of CLIP bleeding. More complex prompts does not mean better results. Keep it simple. Use ADetailer to enhance faces. Basically every solo portrait I made uses it. You can get my settings by clicking on "copy generation data". I suggest you use denoising under 0.3 to avoid getting always the same face. Use BadDream and UnrealisticDream negative embeddings (BadDream, (UnrealisticDream:1.2)). Add weight to UnrealisticDream between 1.2 and 1.5. Do not use FastNegative or EasyNegative if you aim at realism. However, they're good for artworks. Use Highres.fix with the following settings: Denoising strength: 0.45, Hires steps: 20, Hires upscaler: 8x_NMKD-Superscale_150000_G and as much upscale as you can (my gpu only handles up to x1.8 at 512x768 base resolution, but you can go higher). If you don't have 8x_NMKD-Superscale_150000_G you can probably use another GAN, but it should be easy to find on Google. You can also try Latent with a denoise higher than 0.6, but the result will be harder to control. Try to condition faces by prompting for eye colors, hairstyles, hair color, ethnicity and so on. Even celebrity names do work. This model is pretty good at not making a single face if you play with the context.
API PlaygroundAPI Documentation

API Endpoint URL

Base URL for all API requests to this endpoint.

https://modelslab.com/api/v6/images/text2img

API Authentication

Authentication requires a valid API key included in the request. Generate and manage your API keys from your developer dashboard. Include the key in the key parameter for all API requests.

Integration Examples

Production-ready code samples for API integration

{
"prompt": "R3alisticF, hauntingly beautiful oriental necromancer, long flowing brown hair, bangs, darkly tanned skin, earrings, bone necklaces, dark eyeshadow, red lips, vibrant, front-laced transparent, filmy silk blouse, cleavage, holding skull, in a sandstone room lit by candles, High Detail, Perfect Composition, high contrast, silhouetted, chiascuro",
"model_id": "AbsoluteReality",
"lora_model": [],
"width": "1024",
"height": "1024",
"negative_prompt": "(worst quality:2), (low quality:2), (normal quality:2), (jpeg artifacts), (blurry), (duplicate), (morbid), (mutilated), (out of frame), (extra limbs), (bad anatomy), (disfigured), (deformed), (cross-eye), (glitch), (oversaturated), (overexposed), (underexposed), (bad proportions), (bad hands), (bad feet), (cloned face), (long neck), (missing arms), (missing legs), (extra fingers), (fused fingers), (poorly drawn hands), (poorly drawn face), (mutation), (deformed eyes), watermark, text, logo, signature, grainy, tiling, censored, nsfw, ugly, blurry eyes, noisy image, bad lighting, unnatural skin, asymmetry",
"num_inference_steps": "31",
"scheduler": "DPMSolverMultistepScheduler",
"guidance_scale": "7.5",
"enhance_prompt": false,
"key": "YOUR_API_KEY"
}

SDKs

Official SDKs

Production-ready SDKs and client libraries for all major programming languages

API Parameters

Technical specifications for API request parameters.

Field NameParameterTechnical Description
promptpromptprompt help in image generation
Modelmodel_idEnter model_id that can help in image generation
lora Modellora_modelNo description available
Widthwidthwidth of the image
Heightheightheight of the image
Negative Promptnegative_promptNegative prompt help in avoid things that you do not want in image
Stepsnum_inference_stepsNumber of inference steps
SchedulerschedulerSampling scheduler
Guidance Scaleguidance_scaleHow closely to follow the prompt (1-10)
enhance_promptenhance_promptAutomatically enhance the prompt