Anything_to_Real_Characters
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探索 AI 模型 13
Anything_to_Real_Characters_2511
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Anyto3DDonghuaStyle
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Flux2_Klein_Anything_to_Real_Characters
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Klein_AnimeHDupscaling
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Krea-Edit-lora
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Krea2-Anime-Style-Collection
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Krea2_Anything2RealCharacters
WarmBloodAban> 🚀 **Try Online / 在线一键体验** > > Don't have a high-end GPU? You can run and test this model directly on RunningHub without local setup: > > 无需本地部署显卡，点击下方链接即可在 RunningHub 上直接运行与体验该工作流： > 👉 **Click Here to Run on RunningHub / 在线运行链接** > *Special thanks to our community group members for their valuable test feedback! Unless critical issues arise, V3 will serve as the final release for the foreseeable future. For commercial inquiries, feel free to reach out.* 🙏 > ⚡ **Compute Sponsor / 算力支持致谢** > > Special thanks to our compute sponsor for providing the GPU acceleration required to train and fine-tune this 2048px model! > > 本模型的 2048 高清微调训练离不开算力赞助方的大力支持，非常感谢！欢迎扫码关注/支持算力提供方： > > > > > >
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查看详情 ↗krea2-photorealistic-style-collection
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Minimax_H3_LoRAs
WarmBloodAban基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Minimax-h3_Singularity
WarmBloodAban**Minimax-h3_Singularity V2 INT8** builds on V1 with expanded action coverage, stronger prompt adherence, a fix for audio reference conditioning, and enhanced visual style rendering. * ⚔️ **Expanded Action Coverage**: Further optimized on top of V1 to support a wider range of action scenes and more varied motion sequences, extending the model's versatility across dynamic video generation scenarios. * 📝 **Stronger Prompt Adherence**: V2 follows prompt instructions more closely, improving control over subjects, actions, environments, and visual styles. We recommend keeping prompts within approximately **5,000 characters**, using clear, focused descriptions and avoiding excessive or repetitive instructions. * 🎵 **Audio Reference Fix**: Fixed the audio reference conditioning issue. Audio references can now be used to help adjust the character's color tone. * 🎨 **Enhanced Visual Styles**: Strengthened visual style rendering, with strong results across **photorealistic, East Asian realism, 3D CG, and cinematic CG** scenes. For best results, explicitly include the desired style keywords in your prompt. * 📦 **INT8 Release**: The updated V2 model is available in **INT8 format**. Clearly describe the **subject, action, environment, camera movement, and intended visual style**. Keep instructions consistent and prioritize the details that matter most.
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查看详情 ↗Qwen-Image-2.1-LoRAs
WarmBloodAban--- license: apache-2.0 base_model: Qwen/Qwen-Image-2.1 tags: - qwen - qwen-image - image-editing - lora - anime --- This repository is dedicated to LoRA models specifically fine-tuned for the image editing capabilities of `Qwen-Image-2.1`. I will be continuously updating and publishing various functional and stylistic LoRAs here. * **Overview**: A LoRA designed to enhance character consistency during anime-style image editing. * **Training Data**: Primarily fine-tuned on character model sheets (4-view references) and a variety of facial expression edits. * **Status**: ⚠️ **Experimental** > *Note: This model is currently in an experimental phase. It was primarily developed to test and benchmark the optimal training parameters for Qwen Image 2.1. As a result, specific editing outcomes and output stability are not strictly guaranteed.*
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查看详情 ↗Singularity-LTX-2.3_OmniCine_V1
WarmBloodAbanThis is not just a standard fine-tune; it is a fundamental restructuring of the **LTX-Video (2.3)** generation logic. I am thrilled to present the official release of **LTX2.3 Singularity** to the community. This comprehensive optimization framework focuses heavily on **Image-to-Video (I2V)**, **First & Last Frame Control**, and **Reference-to-Video** generation. Although it has currently undergone only nearly **100,000 steps** (calculated by gradient accumulation), its enhancements in physical consistency, dynamic motion, and cinematic expression have already far exceeded expectations. 您的浏览器不支持视频标签。 Prompt:8-second video, one-take shot,this high-octane cinematic animation features a young woman skateboarding down a steep coastal road during a bright, sunny afternoon, evoking a sense of freedom and adrenaline. From 0 to 3 seconds, the girl crouches low on her skateboard, her long brown hair streaming behind her as she accelerates down the incline. Between 4 and 8 seconds, she maintains a steady, aerodynamic posture, skillfully navigating the winding asphalt while her oversized white t-shirt billows in the wind, showing intense focus and excitement. The camera utilizes a low-angle tracking shot from directly behind the skater, moving at a high velocity to create an immersive sense of speed; the composition starts with a wide-angle view of the sprawling coastal city and ocean, then maintains a medium-close-up on the girl's back and the board throughout the descent. The setting is a picturesque Mediterranean-style hillside overlooking a turquoise bay under a vibrant blue sky filled with fluffy white clouds, featuring high-contrast sunlight casting sharp shadows and a warm, high-saturation color palette. The soundscape is dominated by the continuous, high-pitched whirring of skateboard wheels against the pavement and the rushing sound of wind, synchronized with an upbeat, rhythmic electronic background track. Significant motion blur is applied to the road surface and passing scenery to enhance the perception of speed, combined with a sharp focus on the central subject to maintain a polished, professional look，无字幕。 您的浏览器不支持视频标签。 Prompt:Modern anime style, office sett
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查看详情 ↗暂未找到匹配模型
可以调整厂商、分类或输入输出条件；新模型正持续收录。
COST EXPLORER
好模型，也要算好成本。
调整月度 Token 用量，直观比较不同模型的预估 API 开支。
1 M = 100 万 Token · 美元计价
仅比较同一渠道的基础文本 Token 报价
仅比较同一渠道的基础文本 Token 报价
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。
MODEL HANDBOOK
读懂模型，再做选择
API 价格应该怎么比较？+
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。
开放权重，就代表可以免费商用吗？+
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。
排行榜第一，就是最适合我的模型吗？+
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。