4x_foolhardy_Remacri
LyliaEngineCopy the file 4x_foolhardy_Remacri.safetensors inside the folder: stable-diffusion/models/ESRGAN or ComfyUI/models/upscale_models
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从语言到影像,从开源到 API。读懂模型能力、比较真实成本,
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Copy the file 4x_foolhardy_Remacri.safetensors inside the folder: stable-diffusion/models/ESRGAN or ComfyUI/models/upscale_models
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Anima is a 2 billion parameter text-to-image model created via a collaboration between CircleStone Labs and Comfy Org. It is focused mainly on anime concepts, characters, and styles, but is also capable of generating a wide variety of other non-photorealistic content. The model is designed for making illustrations and artistic images, and will not work well at realism. It is trained on several million anime images and about 800k non-anime artistic images. No synthetic data was used for training. The knowledge cut-off date for the anime training data is September 2025. The model is natively supported in ComfyUI. The model files go in their respective folders inside your model directory:
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My first mix in illustrious category aiming to bring more details and flexibility to animated style of this type of models. Various results can be achieved - from animated to semi-realistic style depending on the prompt. Version 2: Cranking up overall details and contrast. Colors look more vivid too. Needs further testing. Has more of its "own identity" compared to version 1.0. Version 1: Overall very decent prompt adherence and anatomy. Stylisticaly close to anime-semirealism. High flexibility: some combinations of LORAs give very interesting results (you can find examples in the images).
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V1 use illustrious-xl as base, versions from 0.2M up are trainined with quality prompts like masterpiece or worst quality. Recommended prompts in negative are "worst quality, bad quality" and masterpiece in positiv. There is also my pony xl variant. Model is trained with images with minimal disruptive features like floating texts, logos, speak bubbles and signatures as possible. If such features appearing in a image, please use prompt "signature" as negative. Excluded metadata and franchise tags, don't use them. meta data -> something like "highres", franchise tags like "re:zero kara hajimeru isekai seikatsu" are pruned on characters like "rem_(re:zero)".
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Pony Diffusion V6 is a versatile SDXL finetune capable of producing stunning SFW and NSFW visuals of various anthro, feral, or humanoids species and their interactions based on simple natural language prompts. CHECK "ABOUT THIS VERSION" ON THE RIGHT IF YOU ARE NOT ON "V6" FOR IMPORTANT INFORMATION. Please join our Discord Server to support development of new versions of this model and get access to free SD bot and check out more examples of this model capabilities on our prompt sharing website or follow the author on Twitter. Important information
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4 Step Lightning Version: Refer to the "About this version" section of the version for more information. 8 Step Lightning Version: Refer to the "About this version" section of the version for more information. I have written an article that explains and provides some useful resources to help you achieve great generation results. You can check it out for detailed insights and recommendations.
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I used approximately a lot of niji v6 style image, the pictures were with style called pseudo-realistic and semi-realism so i tried to focus on this 2 style
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Skin Details: created and merged Loras that add a little more details to skin. Should be more noticeable on realistic Checkpoints. Armor and Weapons Details:: created and merged Loras that adds detailed engraving and patterns. Better material quality. A detail tweaker/booster inspired by the work of many awesome creators like Shed_The_Skin's Detail Slider LoRA, w4r10ck's Detail Tweaker XL, and many, MANY, others.
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WAI_NSFW-illustrious-SDXL_NSFW-illustrious-SDXL_NSFW-illustrious-SDXL_NSFW-illustrious-SDXL-Checkpoint-WAI-Shakker Character Select SAA This is a Stand Alone App with AI prompt, Semi-auto Tag Complete and ComfyUI/WebUI API support. One-Click embedded package In case you don't know how to build your own Python enverment, try the embeded_env_for_SAA Down and unzip to your computer Db-click #run_XX.bat
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可以调整厂商、分类或输入输出条件;新模型正持续收录。
调整月度 Token 用量,直观比较不同模型的预估 API 开支。
使用已采集且单位可比的 USD / 百万 Token 渠道报价。报价为采集时快照;不计缓存优惠、阶梯价、推理额外输出与税费,请以来源的当前报价为准。
先区分输入、输出和缓存价格,再使用同一任务和用量估算总费用。图像、音频和视频可能按张、时长或分辨率计费,不能直接与 Token 单价比较。
不一定。必须逐一核对具体模型版本的许可证、商用限制及使用政策。自己部署还需要考虑显存、推理资源和运维费用。
榜单取决于测试任务、版本与评测方法。建议用实际业务样本比较准确性、时延、稳定性和成本,再选择模型。