Type | |
Stats | 663 0 |
Reviews | (92) |
Published | Mar 30, 2024 |
Base Model | |
Hash | AutoV2 D11AC2E9FA |
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:
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]
为了获得更高质量的结果,请在提示前面加上:
masterpiece, best quality, very aesthetic, absurdres
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
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
模型也完美继承了Animagine XL 3.1字符请参考https://huggingface.co/spaces/cagliostrolab/animagine-xl-3.1/blob/main/wildcard/character31.txt#L13
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)
{
"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"
}
模型使用LyCORIS来模拟ΔW以用来模拟BASE 以下下是LyCORIS脚本命令
python merge.py AnimagineXL 31.safetensors mk_kkk_xl.safetensors FantasyParadise_V1.safetensors --is_sdxl --device cpu --dtype fp16 --weight 1.0
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