原文链接：https://arxiv.org/pdf/2403.14520v2.pdf项目链接：https://sites.google.com/view/cobravlm/论文标题：Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference 方法介绍 模型架构 Cobra 采用了经典的视觉编码器、连接两个模态的投影器和 LLM 语言主干组成的 VLM 结构。
但是,如果仅仅是依赖文本训练的大模型,将不足以适应更多样的任务场景。为此,结合了各种视觉信息、语音信息、文本信息训练得到的多模态大模型(Multimodal Large Language Models,简称MLLM),将是未来大模型的发展趋势。视觉-语言模型(VLMs)作为传统LLMs的自然扩展,通过增强LLMs的视觉信息处理能力,使得模型能够更好地理解...
项目链接:https://sites.google.com/view/cobravlm/ 论文标题:Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference 快点击进入:Mamba和多模态学习技术交流群 CVPR 2024 论文和开源项目合集请戳—>https://github.com/amusi/CVPR2024-Papers-with-Code 方法介绍 模型架构 Cobra 采用...
项目链接:https://sites.google.com/view/cobravlm/ 论文标题:Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference 方法介绍 模型架构 Cobra 采用了经典的视觉编码器、连接两个模态的投影器和 LLM 语言主干组成...
论文标题:Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference 方法介绍 模型架构 Cobra 采用了经典的视觉编码器、连接两个模态的投影器和 LLM 语言主干组成的 VLM 结构。LLM 主干部分采用了 2.8B 参数预训练的 Mamba 语言模型,该模型在 600B token 数量的 SlimPajama 数据集上进...
值得注意的是,Cobra 甚至在参数更少的情况下实现了与 LLaVA 相当的性能,突显了其效率。 论文标题: Cobra:Extending Mamba to Multi-Modal Large Language Model for Efficient Inference 原文链接: https://arxiv.org/pdf/2403.14520v2.pdf 项目链接: https://sites.google.com/view/cobravlm/ 一、方法介绍 1.1...
We give several models an “improved recipe”, inspired by changes adopted by popular large language models such as PaLM (Chowdhery et al. 2023) and LLaMa (Touvron et al. 2023). These include:受到PaLM(Chowdhery 等人,2023 年)和 LLaMa(Touvron 等人,2023 年)等流行大型语言模型所采用的变化的...
Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference 论文链接: https://arxiv.org/pdf/2403.14520.pdf 项目主页: https://sites.google.com/view/cobravlm/ 方法介绍 模型架构 Cobra 采用了经典的视觉编码器、连接两个模态的投影器和 LLM 语言主干组成的 VLM 结构。LLM 主干部分...
In terms of neural networks, the “state” of a system is typically its hidden state and in the context of Large Language Models, one of the most important aspects of generating a new token. What is a State Space Model? SSMs are models used to describe these state representations and ...
Transformers have seen recent popularity with the rise of Large Language Models (LLMs) like LLaMa-2, GPT-4, Claude, Gemini, etc., but it suffers from the problem of context window. The issue with transformers lies in it’s core, the multi head-attention mechanism. ...