FantasyParadise模型基于Animagine XL 3.1 训练而成延续了Animagine XL 3.1 出图方式和参数推荐设置要引导模型生成高美感图像，请使用负面提示，例如：<pre><code>nsfw, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]</code></pre>为了获得更高质量的结果，请在提示前面加上：<pre><code>masterpiece, best quality, very aesthetic, absurdres</code></pre>建议使用大约 5-7 的CFG ，采样步骤低于 30，并使用 Euler Ancestral （Euler a） 作为采样器。多方面分辨率此模型支持生成以下维度的图像：尺寸 纵横比<pre><code>1024 x 1024	1：1 

1152 x 896	9:7

896 x 1152	7:9

1216 x 832	19:13

832 x 1216	13:19

1344 x 768	7：4 

768 x 1344	4：7 

1536 x 640	12：5 

640 x 1536	5：12</code></pre>模型也完美继承了Animagine XL 3.1字符请参考<a target="_blank" rel="ugc" href="https://huggingface.co/spaces/cagliostrolab/animagine-xl-3.1/blob/main/wildcard/character31.txt#L13">https://huggingface.co/spaces/cagliostrolab/animagine-xl-3.1/blob/main/wildcard/character31.txt#L13</a>模型继承了Animagine XL 3.0，Animagine XL 3.1许可证基于 Animagine XL 3.0，Animagine XL 3.1 属于 Fair AI 公共许可证 1.0-SD 许可证，该许可证与 Stable Diffusion 模型的许可证兼容。要点：修改共享：如果您修改 FantasyParadise_V1，您必须共享您的更改和原始许可证。源代码可访问性：如果您修改后的版本可通过网络访问，请为其他人提供获取源代码的方法（如下载链接）。这也适用于派生模型。分发条款：任何发行版都必须遵循此许可证或其他具有类似规则的许可证。合规：不合规必须在 30 天内解决，以避免许可证终止，强调透明度和遵守开源价值观。选择此许可证旨在保持 Animagine XL 3.1 的开放性和可修改性，与开源社区精神保持一致。它保护贡献者和用户，鼓励协作、合乎道德的开源社区。这确保了该模型不仅受益于公共输入，而且还尊重开源开发自由。以下是训练参数训练参数（Training parameters）<pre><code>{

 "ss_sd_model_name": "animagine-xl-3.1.safetensors",

 "ss_resolution": "(1024, 1024)",

 "ss_clip_skip": "2",

 "ss_num_train_images": "6110",

 "ss_caption_dropout_every_n_epochs": "0",

 "sshs_legacy_hash": "f78d97b7",

 "ss_text_encoder_lr": "1e-05",

 "ss_multires_noise_iterations": "None",

 "ss_lowram": "False",

 "ss_zero_terminal_snr": "False",

 "ss_total_batch_size": "5",

 "ss_color_aug": "False",

 "ss_bucket_no_upscale": "False",

 "ss_ip_noise_gamma": "None",

 "ss_max_train_steps": "12220",

 "ss_num_batches_per_epoch": "1222",

 "ss_noise_offset": "None",

 "ss_scale_weight_norms": "None",

 "ss_keep_tokens": "0",

 "ss_num_epochs": "10",

 "ss_enable_bucket": "True",

 "ss_steps": "12220",

 "ss_optimizer": "bitsandbytes.optim.adamw.AdamW8bit",

 "ss_base_model_version": "sdxl_base_v1-0",

 "ss_lr_scheduler": "cosine_with_restarts",

 "ss_network_dropout": "None",

 "modelspec.prediction_type": "epsilon",

 "ss_learning_rate": "0.0001",

 "ss_network_alpha": "1.0",

 "ss_max_grad_norm": "1.0",

 "ss_min_bucket_reso": "256",

 "ss_gradient_checkpointing": "True",

 "ss_seed": "1026",

 "ss_face_crop_aug_range": "None",

 "ss_batch_size_per_device": "5",

 "ss_cache_latents": "True",

 "ss_shuffle_caption": "True",

 "modelspec.architecture": "stable-diffusion-xl-v1-base/lora",

 "modelspec.implementation": "https://github.com/Stability-AI/generative-models",

 "ss_sd_model_hash": "c798d390",

 "modelspec.sai_model_spec": "1.0.0",

 "ss_num_reg_images": "0",

 "ss_mixed_precision": "fp16",

 "ss_v2": "False",

 "ss_adaptive_noise_scale": "None",

 "ss_gradient_accumulation_steps": "1",

 "ss_caption_tag_dropout_rate": "0.1",

 "ss_output_name": "mk_kkk_xl",

 "sshs_model_hash": "0f6161a4645a9159bfdc2296d55f6c606bd37385d5b422d758220789d05e89ee",

 "ss_reg_dataset_dirs": {},

 "ss_max_bucket_reso": "4997",

 "modelspec.title": "mk_kkk_xl",

 "ss_flip_aug": "False",

 "ss_new_sd_model_hash": "e3c47aedb06418c6c331443cd89f2b3b3b34b7ed2102a3d4c4408a8d35aad6b0",

 "ss_full_fp16": "True",

 "ss_max_token_length": "225",

 "ss_training_started_at": "1711772016.6059477",

 "ss_min_snr_gamma": "None",

 "ss_random_crop": "False",

 "ss_training_finished_at": "1711798891.3724864",

 "ss_network_dim": "10000000",

 "ss_unet_lr": "0.0001",

 "ss_debiased_estimation": "True",

 "ss_lr_warmup_steps": "50",

 "ss_multires_noise_discount": "0.3",

 "ss_dataset_dirs": {

 "10_sc": {

 "n_repeats": 10,

 "img_count": 611

 }

 },

 "ss_sd_scripts_commit_hash": "77568ece5c8d4334cc204d34e148dd20f01c2348",

 "ss_epoch": "10",

 "ss_training_comment": "this LoRA model created from bdsqlsz by bdsqlsz'script",

 "modelspec.encoder_layer": "2",

 "modelspec.date": "2024-03-30T19:41:31",

 "ss_prior_loss_weight": "1.0",

 "ss_network_args": {

 "algo": "lokr",

 "use_scalar": "True",

 "train_norm": "True",

 "conv_dim": "4",

 "conv_alpha": "1",

 "use_tucker": "True",

 "preset": "attn-mlp",

 "factor": "8",

 "dropout": null

 },

 "ss_network_module": "lycoris.kohya",

 "modelspec.resolution": "1024x1024",

 "ss_session_id": "536501796",

 "ss_caption_dropout_rate": "0.0"

}</code></pre>模型使用LyCORIS来模拟ΔW以用来模拟BASE 以下下是LyCORIS脚本命令<pre><code>python merge.py AnimagineXL 31.safetensors mk_kkk_xl.safetensors FantasyParadise_V1.safetensors --is_sdxl --device cpu --dtype fp16 --weight 1.0</code></pre>模型用途声明1. 你不得将此模型及其衍生版本（如融合模型版本）托管于计划赚取收入或捐赠的网站/应用程序。如果您需要将此模型及其衍生版本用于商业目的（如生成式服务、售卖图片、将图片用于公开发表到短视频平台的文章或出版物等等）2. 您不得直接售卖由此模型生成的图片，除非您对该图片进行了足够程度的人工修改，使其在法律意义上可以被完全判定为您的个人作品。如果您违反本条，所造成的一切法律后果由您个人承担，请恕本人概不负责。3. 您不能使用该模型故意制作或共享非法或有害的内容传播和输出，请您遵守公序良德，将此模型用于积极正面的用途。本模型中不包含任何真人素材图像源和训练代码来自互联网，模型仅用于科研兴趣交流

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