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CLIP 模型是 OpenAI 在大规模图像-文本对数据集上通过对比学习方式训练的图文模型,具体论文可以参考 [2103.00020] Learning Transferable Visual Models From Natural Language Supervision,对应的代码库为 GitHub - openai/CLIP: CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet giv...
Usage example of Long-CLIP Checkpoints of Long-CLIP 🛠️ Usage Installation Our model is based onCLIP, please prepare environment for CLIP. how to use Please first clone ourrepofrom github by running the following command. git clone https://github.com/beichenzbc/Long-CLIP.gitcdLong-CLIP ...
而Long-CLIP无需任何训练,可以即插即用地替换CLIP作为文本编码器。Long-CLIP既可以突破77个token的限制,实现篇章级别的图像生成(右下),也可以在77个token内建模更多地细节,实现细粒度图像生成(右上)。而对于简单的短文本(左),由于Long-CLIP保持了CLIP的特征空间,可以和原始的CLIP生成相同的内容,图像质量不会产生退...
上图直观地展示了Long-CLIP模型训练过程的流程图,其中包括了两个关键的子模块:细粒度图像特征与长详细描述的对齐,以及粗粒度图像特征与短摘要描述的对齐。 细粒度图像特征与长详细描述的对齐: 这一步骤的目的是通过训练模型来使图像的细粒度特征与长文本描述相匹配。这意味着模型需要捕捉图像中的所有细节,并理解这些...
论文名:Long-CLIP: Unlocking the Long-Text Capability of CLIP 论文链接:arxiv.org/pdf/22403.153 开源代码:github.com/beichenzbc/L 引言 对比性语言-图像预训练(CLIP)是一个包含文本编码器和图像编 码器的视觉语言基础模型。它基于对比学习对视觉和语言模态进行对齐, 在下游任务中被广泛采用,例如零样本分类、...
code:https://github.com/beichenzbc/long-clip keywords: #多模态 #Zero-Shot #text-image-retrieval importance: #star3 TLDR: 问题: clip,文本部分是a bag of concepts. 因为大部分文本比较短,位置比较高的地方position没有训练好。本来限制的长度是77. 实际上有效的长度,只有前边的20. 这使得 CLIP 无法处...
git clone https://github.com/comfyanonymous/ComfyUI.git cd ComfyUI/custom_nodes git clone git@github.com:SeaArtLab/ComfyUI-Long-CLIP.git DownloadLongCLIP-Lto models/checkpoints, and thanks toLong-CLIPfor making the weights available. Once the LongCLIP-G weights are released, we will also ...
Long-CLIP可以突破77个token的限制,实现篇章级别的图像生成(右下)。 也可以在77个token内建模更多地细节,实现细粒度图像生成(右上)。 论文链接: https://arxiv.org/abs/2403.15378 代码链接: https://github.com/beichenzbc/Long-CLIP —完— 评选报名即将截止!
git clone https://github.com/comfyanonymous/ComfyUI.git cd ComfyUI/custom_nodes git clone git@github.com:SeaArtLab/ComfyUI-Long-CLIP.git 下载LongCLIP-L到 models/checkpoints,同时感谢Long-CLIP开放权重,后续LongCLIP-G权重开放后,我们会同步支持!