han2han-rl
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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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**Animagine XL 3.0** is the latest version of the sophisticated open-source anime text-to-image model, building upon the capabilities of its predecessor, Animagine XL 2.0. Developed based on Stable Diffusion XL, this iteration boasts superior image generation with notable improvements in hand anatomy, efficient tag ordering, and enhanced knowledge about anime concepts. Unlike the previous iteration, we focused on training the model to learn concepts rather than just aesthetics. - **Developed by**: Cagliostro Research Lab - **Model type**: Diffusion-based text-to-image generative model - **Model Description**: Animagine XL 3.0 is engineered to generate high-quality anime images from textual prompts. It features enhanced hand anatomy, better concept understanding, and prompt interpretation, making it the most advanced model in its series. - **License**: CreativeML Open RAIL++-M License - **Finetuned from model**: Animagine XL 2.0 Animagine XL 3.0 is accessible through user-friendly platforms such as Gradio and Google Colab:
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.title-container { display: flex; justify-content: center; align-items: center; height: 100vh; } .title { font-size: 2.5em; text-align: center; color: #333; font-family: 'Helvetica Neue', sans-serif; text-transform: uppercase; letter-spacing: 0.1em; padding: 0.5em 0; background: transparent; } .title span { background: -webkit-linear-gradient(45deg, #7ed56f, #28b485); -webkit-background-clip: text; -webkit-text-fill-color: transparent; }
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**Animagine XL 4.0**, also stylized as **Anim4gine**, is the ultimate anime-themed finetuned SDXL model and the latest installment of Animagine XL series. Despite being a continuation, the model was retrained from Stable Diffusion XL 1.0 with a massive dataset of 8.4M diverse anime-style images from various sources with the knowledge cut-off of January 7th 2025 and finetuned for approximately 2650 GPU hours. Similar to the previous version, this model was trained using tag ordering method for the identity and style training. With the release of **Animagine XL 4.0 Opt (Optimized)**, the model has been further refined with an additional dataset, improving **stability**, **anatomy accuracy**, **noise reduction**, **color saturation**, and **overall color accuracy**. These enhancements make **Animagine XL 4.0 Opt** more consistent and visually appealing while maintaining the signature quality of the series. - 2025-02-13 – Added Animagine XL 4.0 Opt - Better stability for more consistent outputs - Enhanced anatomy with more accurate proportions - Reduced noise and artifacts in generations - Fixed low saturation issues, resulting in richer colors - Improved color accuracy for more visually appealing results - 2025-01-24 – Initial release - **Developed by**: Cagliostro Research Lab - **Model type**: Diffusion-based text-to-image generative model - **License**: CreativeML Open RAIL++-M - **Model Description**: This is a model that can be used to generate and modify specifically anime-themed images based on text prompt - **Fine-tuned from**: Stable Diffusion XL 1.0
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It is BERT-base model pre-trained with indonesian Wikipedia and indonesian newspapers using a masked language modeling (MLM) objective. This model is uncased. This is one of several other language models that have been pre-trained with indonesian datasets. More detail about its usage on downstream tasks (text classification, text generation, etc) is available at Transformer based Indonesian Language Models This model was pre-trained with 522MB of indonesian Wikipedia and 1GB of indonesian newspapers. The texts are lowercased and tokenized using WordPiece and a vocabulary size of 32,000. The inputs of the model are then of the form:
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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。