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zai-org/cogvlm-grounding-base-hf

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zai-org/cogvlm-grounding-base-hf

CogVLM 是一个强大的开源视觉语言模型(VLM)。CogVLM-17B 拥有 100 亿视觉参数和 70 亿语言参数,在 10 个经典跨模态基准测试上取得了 SOTA 性能,包括 NoCaps、Flicker30k captioning、RefCOCO、RefCOCO+、RefCOCOg、Visual7W、GQA、ScienceQA、VizWiz VQA 和 TDIUC,而在 VQAv2、OKVQA、TextVQA、COCO captioning 等方面则排名第二,超越或与 PaLI-X 55B 持平。您可以通过线上 demo 体验 CogVLM 多模态对话。 CogVLM is a powerful open-source visual language model (VLM). CogVLM-17B has 10 billion vision parameters and 7 billion language parameters. CogVLM-17B achieves state-of-the-art performance on 10 classic cross-modal benchmarks, including NoCaps, Flicker30k captioning, RefCOCO, RefCOCO+, RefCOCOg, Visual7W, GQA, ScienceQA, VizWiz VQA and TDIUC, and rank the 2nd on VQAv2, OKVQA, TextVQA, COCO captioning, etc., surpassing or matching PaLI-X 55B. CogVLM can also chat with you about images. CogVLM 模型包括四个基本组件:视觉变换器(ViT)编码器、MLP适配器、预训练的大型语言模型(GPT)和一个视觉专家模块。更多细节请参见Paper。 CogVLM model comprises four fundamental components: a vision transformer (ViT) encoder, an MLP adapter, a pretrained large language model (GPT), and a visual expert module. See Paper for more details. The code in this repository is open source under the Apache-2.0 license, while the use of the CogVLM model weights must comply with the Model…

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