ModelsLab/ - HelloWorld XL 6.0

helloworldxl60

Text to Image Community ModelFree for Premium Users LLMs.txt

HelloWorld 6.0 Update - April 20, 2024

Thank you for your patience. I have been job hunting recently, which caused some delays in the HelloWorld updates. Here are the main updates in version 6.0:

HelloWorld 6.0 is an iterative improvement based on version 5.0. Based on my own testing, the realism effect is not significantly different from version 5.0. The main advantage of version 6.0 lies in its broader coverage of concepts in the training set. According to feedback, enhancements have been made in various themes including surrealism, boudoir, group photos, masks, origami, 3D renders, cars, dragons, and maternity photography. Some examples are provided in the illustrations.
HelloWorld 6.0 intentionally includes some low-quality images in the training to enhance the model's response to negative prompts. It is recommended to use the following terms in negative prompts: "low quality, jpeg artifacts, blurry, poorly drawn, ugly, worst quality".
The main body of the HelloWorld 6.0 training set employs GPT4v tagging. For images that GPT4v cannot tag, cogVQA guided by blip2-opt-6.7b is used for tagging. The tagging language style of these multimodal models differs significantly from the traditional WD1.4 tagger. To facilitate more accurate triggering of different concepts in the training set, I have compiled the top 250 high-frequency tagging words from the HelloWorld 6.0 training set. You can view these high-frequency words in this document.

Finally, although SD3 is about to be released, I will still update to HelloWorld XL 7.0, hoping to achieve greater enhancements in version 7.0!

API Playground API 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": "helloworldxl60",
  "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

JavaScript

Python

PHP

API Parameters

Technical specifications for API request parameters.

Field Name	Parameter	Technical Description
prompt	`prompt`	prompt help in image generation
Model	`model_id`	Enter model_id that can help in image generation
lora Model	`lora_model`	No description available
Width	`width`	width of the image
Height	`height`	height of the image
Negative Prompt	`negative_prompt`	Negative prompt help in avoid things that you do not want in image
Steps	`num_inference_steps`	Number of inference steps
Scheduler	`scheduler`	Sampling scheduler
Guidance Scale	`guidance_scale`	How closely to follow the prompt (1-10)
enhance_prompt	`enhance_prompt`	Automatically enhance the prompt