anime-painter
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗DISCOVER & COMPARE
探索 AI 模型 7
Hello, I am very happy to announce the controlnet-canny-sdxl-1.0 model, **a very powerful controlnet that can generate high resolution images visually comparable with midjourney**. The model was trained with large amount of high quality data(over 10000000 images), with carefully filtered and captioned(powerful vllm model). Besides, useful tricks are applied during the training, including date augmentation, mutiple loss and multi resolution. With only 1 stage training, the performance outperforms the other opensource canny models ([diffusers/controlnet-canny-sdxl-1.0], [TheMistoAI/MistoLine]). I release it and hope to advance the application of stable diffusion models. Canny is one of the most important ControlNet series models and can be applied to many jobs associated with drawing and designing. - **Developed by:** xinsir - **Model type:** ControlNet_SDXL - **License:** apache-2.0 - **Finetuned from model [optional]:** stabilityai/stable-diffusion-xl-base-1.0 prompt: A closeup of two day of the dead models, looking to the side, large flowered headdress, full dia de Los muertoe make up, lush red lips, butterflies, flowers, pastel colors, looking to the side, jungle, birds, color harmony , extremely detailed, intricate, ornate, motion, stunning, beautiful, unique, soft lighting
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗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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价格待核验多模态与渠道费用须分别核对
查看详情 ↗- **Developed by:** xinsir - **Model type:** ControlNet_SDXL - **License:** apache-2.0 - **Finetuned from model [optional]:** stabilityai/stable-diffusion-xl-base-1.0 thanks feiyuuu for report the problem. When using the default pose line the performance may be unstable, this is because the pose label use more thick line in training to have a better look. This difference can be fix by using the following method: Find the util.py in controlnet_aux python package, usually the path is like: /your anaconda3 path/envs/your env name/lib/python3.8/site-packages/controlnet_aux/open_pose/util.py Replace the draw_bodypose function with the following code:
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗The following five lines are using different control lines, from top to below, Scribble, Canny, HED, PIDI, Lineart Hello, I am very happy to announce the controlnet-scribble-sdxl-1.0 model, **a very powerful controlnet that can generate high resolution images visually comparable with midjourney**. The model was trained with large amount of high quality data(over 10000000 images), with carefully filtered and captioned(powerful vllm model). Besides, useful tricks are applied during the training, including date augmentation, mutiple loss and multi resolution. Note that this model can achieve higher aesthetic performance than our Controlnet-Canny-Sdxl-1.0 model, the model support any type of lines and any width of lines, the sketch can be very simple and so does the prompt. This model is more general and good at generate visual appealing images, The control ability is also strong, for example if you are unstatisfied with some local regions about the generated image, draw a more precise sketch and give a detail prompt will help a lot. **Note the model also support lineart or canny lines, you can try it and will get a surpurise!!!** - **Developed by:** xinsir - **Model type:** ControlNet_SDXL - **License:** apache-2.0 - **Finetuned from model [optional]:** stabilityai/stable-diffusion-xl-base-1.0
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗controlnet-tile-sdxl-1.0
xinsircode reference: https://huggingface.co/TTPlanet/TTPLanet_SDXL_Controlnet_Tile_Realistic/blob/main/TTP_tile_preprocessor_v5.py https://github.com/lllyasviel/ControlNet-v1-1-nightly/blob/main/gradio_tile.py
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗- Use bucket training like novelai, can generate high resolutions images of any aspect ratio - Use large amount of high quality data(over 10000000 images), the dataset covers a diversity of situation - Use re-captioned prompt like DALLE.3, use CogVLM to generate detailed description, good prompt following ability - Use many useful tricks during training. Including but not limited to date augmentation, mutiple loss, multi resolution - Use almost the same parameter compared with original ControlNet. No obvious increase in network parameter or computation. - Support 10+ control conditions, no obvious performance drop on any single condition compared with training independently - Support multi condition generation, condition fusion is learned during training. No need to set hyperparameter or design prompts. - Compatible with other opensource SDXL models, such as BluePencilXL, CounterfeitXL. Compatible with other Lora models. ***We design a new architecture that can support 10+ control types in condition text-to-image generation and can generate high resolution images visually comparable with midjourney***. The network is based on the original ControlNet architecture, we propose two new modules to: 1 Extend the original ControlNet to support different image conditions using the same network parameter. 2 Support multiple conditions input without increasing computation offload, which is especially important for designers who want to edit image in detail, different conditions use the same condition encoder, without adding extra computations or parameters. We do thoroughly experiments on SDXL and achieve superior performance both in control ability and aesthetic score. We release the method and the model to the open source community to make everyone can enjoy it. Inference scripts and more details can found: https://github.com/xinsir6/ControlNetPlus/tree/main
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价格待核验多模态与渠道费用须分别核对
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。