Anything_to_Real_Characters
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言語から画像、オープンウェイトからAPIまで。能力と実際の費用を比較。
次のアイデアに合うAIを見つけましょう。
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> 🚀 **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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**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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--- 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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This 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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提供元・分類・入出力の条件を変更してください。新しいモデルを随時追加しています。
月間トークン数を調整してAPI費用を比較。
収集済みの比較可能な100万トークン当たり米ドル料金です。キャッシュ割引、段階料金、追加推論出力、税金は含みません。最新料金は出典で確認してください。
入力・出力・キャッシュ料金を分け、同じ用途と使用量で総費用を比較します。画像・音声・動画は枚数、時間、解像度で課金される場合があります。
必ずしもそうではありません。バージョンごとのライセンス、商用制限、ポリシーを確認してください。自前運用には計算資源と保守費用も必要です。
順位はテスト、バージョン、評価方法によります。実際の業務データで精度、遅延、安定性、費用を比較してください。