MODEL PROFILE · 模型档案

FLUX.1-dev-ControlNet-Union-Pro-2.0

Shakker-Labs · FLUX.1-dev-ControlNet-Union-Pro-2.0

This repository contains an unified ControlNet for FLUX.1-dev model released by Shakker Labs. We provide an online demo. A FP8 quantized version provided by community can be found in ABDALLALSWAITI/FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8. In comparison with Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro, - Remove mode embedding, has smaller model size. - Improve on canny and pose, better control and aesthetics. - Add support for soft edge. Remove support for tile. - This ControlNet consists of 6 double blocks and 0 single block. Mode embedding is removed. - We train the model from scratch for 300k steps using a dataset of 20M high-quality general and human images. We train at 512x512 resolution in BFloat16, batch size = 128, learning rate = 2e-5, the guidance is uniformly sampled from [1, 7]. We set the text drop ratio to 0.20. - This model supports multiple control modes, including canny, soft edge, depth, pose, gray. You can use it just as a normal ControlNet. - This model can be jointly used with other ControlNets.

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上下文窗口来源未披露
输入 → 输出文本 → 图像
模型权重待核验
档案更新时间2026/11/2 19:17:06
OVERVIEW

模型介绍

This repository contains an unified ControlNet for FLUX.1-dev model released by Shakker Labs. We provide an online demo. A FP8 quantized version provided by community can be found in ABDALLALSWAITI/FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8. In comparison with Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro, - Remove mode embedding, has smaller model size. - Improve on canny and pose, better control and aesthetics. - Add support for soft edge. Remove support for tile. - This ControlNet consists of 6 double blocks and 0 single block. Mode embedding is removed. - We train the model from scratch for 300k steps using a dataset of 20M high-quality general and human images. We train at 512x512 resolution in BFloat16, batch size = 128, learning rate = 2e-5, the guidance is uniformly sampled from [1, 7]. We set the text drop ratio to 0.20. - This model supports multiple control modes, including canny, soft edge, depth, pose, gray. You can use it just as a normal ControlNet. - This model can be jointly used with other ControlNets.

主要特点

特点摘要待依据来源补齐,不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价,不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价,请查阅来源渠道。

按月估算基础 Token 费用

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预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用?

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗?

不是实时结算价格,而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

许可证:other。模型介绍与第三方评测均以原来源的具体版本和方法为准。