LEOSAM's HelloWorld XL

HelloWorld 7.0 Update - June 13, 2024One-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:<ol><li>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".</li><li>Extracted the fine-tuned LoRA from the<a target="_blank" rel="ugc" href="https://huggingface.co/SPO-Diffusion-Models/SPO-SDXL_4k-p_10ep"> official SPO model</a> 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 &amp; contrast and beautify images. Thanks to the technical team behind SPO.</li><li>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:<pre><code>(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</code></pre></li><li>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:<pre><code>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</code></pre></li></ol>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 <a target="_blank" rel="ugc" href="https://picturesque-soup-93d.notion.site/LEOSAM-HelloWorld-6-0-Top-250-High-Frequency-Tagging-Word-List-1be4971bafb84c22a231ee2f6da29cc1">High-Frequency Tagging Word List of HelloWorld 6.0</a>. 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!

leosamsHelloworldXL_helloworldXL70.safetensors

HelloWorld XL 7.0

HelloWorld XL 6.0

HW5.0_Euler_a_Lightning

HelloWorld XL 5.0 GPT4V

HelloWorld XL 4.0

HelloWorld XL 3.2 DPO

HelloWorld XL 3.0

HelloWorld XL 2.0

HelloWorld XL 1.0

Film Grain 2.0

Film Grain 1.0

Utopia 3.0

Utopia 2.0

Utopia

Reality 3.0

Fantasy2.0

Reality2.0

Reality

Fantasy

Files with SHA256: 573f4a7d356453549938666f1b9d58df23a2a8e12efd82d674d32faf28212845