🎉 New Year Sale: Get 20% OFF on all plans — Use code NEWYEAR2026.

Upgrade now
LEOSAM's HelloWorld XL - HelloWorld XL 7.0 thumbnail

ModelsLab/LEOSAM'S HelloWorld XL - HelloWorld XL 7.0

leosamshelloworldxl-helloworldxl70
Text to Image Community ModelFree for Premium UsersLLMs.txt

HelloWorld 7.0 Update - June 13, 2024

One-sentence update summary: HelloWorld 7.0 is an iteratively optimized version, with the best body performance in the entire series, and further enhanced concept scope and detail richness.

Update details:

  1. By adding negative training images, strengthening pose training, and optimizing the clip model, the accuracy of the model's limbs and hands has been improved compared to previous versions. The recommended negative prompt words are: "bad hand, bad anatomy, worst quality, ai generated images, low quality, average quality".

  2. Extracted the fine-tuned LoRA from the official SPO model and incorporated it into HelloWorld 7.0. SPO is a further improvement of the DPO method. The SPO base model is used for better performance than the DPO XL base model and the original SDXL base model. The SPO LoRA can enhance image details & contrast and beautify images. Thanks to the technical team behind SPO.

  3. Continued to expand the concept scope of the training set, but optimized and streamlined the training set (large training set fine-tuning is too expensive, and H800 is difficult to rent recently, can't afford the local training time). The current total training set is 20,821 images. The training set resolution distribution is as follows, and it is recommended to use several resolutions with a larger number of images for output:

    (832, 1248) - Count: 7128
    (896, 1152) - Count: 6250
    (1248, 832) - Count: 2402
    (1024, 1024) - Count: 1639
    (1360, 768) - Count: 928
    (1152, 896) - Count: 870
    (768, 1360) - Count: 432
    (960, 1088) - Count: 506
    (992, 1056) - Count: 162
    (1088, 960) - Count: 140
    (704, 1472) - Count: 120
    (1056, 992) - Count: 122
    (1472, 704) - Count: 115
    (1632, 640) - Count: 75
    (640, 1632) - Count: 12
  4. Used GPT4O to re-label all datasets. This time, a structured labeling method was used, with the specific structure being: "one-sentence summary description + multiple image element tags + inspired by XXX + aesthetic quality description words", where the aesthetic quality description words are divided into five levels: worst quality, low quality, average quality, best quality, and masterpiece. A typical labeling example is as follows:

    conceptual art featuring a human hand wrapped in red and beige ribbons, isolated against a plain, light background, realistic style, minimalist color scheme, smooth textures, elongated and surreal aesthetic, inspired by salvador dalí's surrealist works, masterpiece

The "High-Frequency Tagging Word List" and the "High-Frequency Art Style List" involved in the Inspired by XXX for the HelloWorld 7.0 version will only be provided to commercial licensing users. Partners who have purchased Helloworld XL series model authorization in the past, please contact me if there are any omissions to get it for free.

Players can refer to the High-Frequency Tagging Word List of HelloWorld 6.0. In addition, I have also provided 150+ high-quality HelloWorld 7.0 example images in the gallery, which can be used as a reference for everyone's output. Model making is not easy, thank you players for your understanding and tolerance!

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": "leosamshelloworldxl-helloworldxl70",
"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