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        "description": "<!--\nRead the user guide below![HuggingFace Backup link]\n\nAingDiffusion XL (read: Ah-eeng Diffusion XL) merges anime models based on SDXL with some extra self-trained datasets. This model is capable of generating high-quality anime images.\n\n\n\nGuide to generating good images with this model(This guide is relevant to the latest version of AingDiffusion XL)\n\n* This model uses Animagine's way of prompting:\n\n`1girl/1boy, character name, from what series, what style, everything else in any order, masterpiece, best quality, very aesthetic, absurdres`It is also recommended to include the style name of the images you want to generate in the prompt (eg. anime screencap, sketch, pixel art, famous artist name, etc.).\n\n\n\nThe standard negative prompt recommended for this model:\n\n`nsfw, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, watermark, artistic error, username, scan, [abstract],`* Use SDXL-recommended resolutions. This is SDXL, SD 1.5 resolution always performs worse.\n\n* The recommended sampler is \"Euler a\" with ~7 CFG and ~25 steps.\n\n* Set ENSD (eta noise seed delta) to 31337 [to replicate image].\n\n\n\nCharacter ListAingDiffusion XL is a derivative of Animagine XL v3. The latest version of AingDiffusion XL is a derivative of Animagine XL 3.1, which has over 4.9k characters trained on it. You can see the full list here: https://huggingface.co/spaces/cagliostrolab/animagine-xl-3.1/blob/main/wildcard/characterfull.txt\n\n\n\nAingDiffusion XL v1.2 Nerd FactsThe fine-tuned layer dataset count has been increased from 7.7k images to 19.8k images, which improves the quality of the model.\n\n\n\n## Fine-tune Dataset Details\n\n\n\n- Raw dataset size: 33,704 images\n\n- Processed with `aesthetic-shadow-v2`\n\n- Total `lq` dataset: 13.814 images\n\n- Total `hq` dataset: 19,890 images\n\n- Only the `hq`-rated dataset is used for training.\n\n\n\n## First Layer Finetune Details\n\n\n\n- Dataset count: 19,890 images\n\n- Batch size: 8\n\n- Gradient Accumulation: 3\n\n- Equivalent batch size: 24\n\n- Epoch: 8\n\n- Used epoch: 5\n\n\n\n- LyCORIS Network: LoCon\n\n- Network Dim: 16\n\n- Network Alpha: 8\n\n- Conv Dim: 8\n\n- Conv Alpha: 4\n\n- Optimizer: AdamW\n\n- LR Scheduler: Cosine with restarts\n\n- Restarts: 3\n\n- Unet LR: 5e-04\n\n- Text Encoder LR: 25e-5\n\n- Min SNR gamma: 5\n\n- Other optimizer arguments:\n\n - Betas: 0.9, 0.99\n\n - Weight_decay: 0.1\n\n\n\nThis LyCORIS was merged with Animagine XL 3.1 with full weight. The result was then diluted with Animagine XL 3.1 with half weight.\n\n\n\n## Second Layer Finetuning Details\n\n\n\n- Dataset count: 19,890 images\n\n- Batch size: 8\n\n- Gradient Accumulation: 3\n\n- Equivalent batch size: 24\n\n- Epoch: 10\n\n- Used epoch: 10\n\n\n\n- LyCORIS Network: LoCon\n\n- Network Dim: 16\n\n- Network Alpha: 8\n\n- Conv Dim: 8\n\n- Conv Alpha: 4\n\n- Optimizer: AdamW\n\n- LR Scheduler: Cosine annealing warmup restarts\n\n- Restarts: 10\n\n- Min. LR: 1e-06\n\n- Unet LR: 1e-05\n\n- Text Encoder LR: 1e-05\n\n- Min SNR gamma: 5\n\n- Other optimizer arguments:\n\n - Betas: 0.9, 0.99\n\n - Weight_decay: 0.1\n\n\n\nThis LyCORIS was then merged with the diluted first layer finetune with full weight.\n\n\n\nFAQQ: There's nothing special about this model, it didn't have something unique.\n\nA: The goal of AingDiffusion XL right now is to enhance the experience and the capabilities of Animagine. The goal is basically to make Animagine on steroids.\n\n\n\nQ: The images I generate are bad and not as good as yours.\n\nA: First, make sure you follow the standard prompting guide I provide. Also, sometimes I found people using SD 1.5 embeddings with this model. DO NOT USE THEM. THEY DON'T WORK WITH SDXL.\n\n\n\nLegalsDue to the usage of Animagine XL with the merge, the model is now using Fair AI Public License 1.0-SD license.\n\nBecause of some reason, I decided to make the merging recipe clearer which I will put in the \"About Version\" section starting from version v0.6.\n-->",
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