E5-V: Universal Embeddings with Multimodal Large Language Models OverviewWe propose a framework, called E5-V, to adpat MLLMs for achieving multimodal embeddings. E5-V effectively bridges the modality gap between different types of inputs, demonstrating strong performance in multimodal embeddings even ...
from sentence_transformers import SentenceTransformer e5 = SentenceTransformer("intfloat/multilingual-e5-large") e5.save("multilingual-e5-large") Run TEI on the exported model. The server does not start and emits the following: tokenizer.json not found. text-embeddings-inference only supports fast ...
3亿模型参数的E5-large效果超过了餐数量达48亿的GTR-xxl跟Sentence-T5-xxl。 b) BERT-FT-base跟E5-base的差别在于后者多了一个在CCPairs数据集预训练的阶段,两者性能之间的显著差异也论证了在CCPairs数据进行对比学习预训练的价值。 图2: MTEB评测结果 c) 高质量的预训练数据对于整体性能体现明显,对网上搜集到...
下载地址 https://github.com/helm/helm/releases AI检测代码解析 # 下载包 $ wget https://get.helm.sh/helm-v3.9.4-linux-amd64.tar.gz # 解压压缩包 $ tar -xf helm-v3.9.4-linux-amd64.tar.gz # 制作软连接 $ ln -s /opt/helm/linux-amd64/helm /usr/local/bin/helm # 验证 $ helm ve...
未必能跟上一周两期的速度,可能会跳更,或者摆烂机翻直出( 听写:Faster-Whisper-XXL + faster-whisper-large-v2 https://github.com/Purfview/whisper-standalone-win 翻译:VoiceTransl + DeepSeek-chat @昕蒲Simple https://github.com/shinnpuru/VoiceTransl 字幕样式来自@MetricSubs字幕组 手工优化断句,AI辅助...
这个github存储库包括以下多个shufflenet模型: shufflenet:一种非常有效的移动设备卷积神经网络 shufflenetv2:高效cnn架构设计的实用指南 shufflenetv2+:shufflenetv2的增强版本 shufflenetv2.large:一个基于shufflenetv2的更深版本。 OneShot:均匀采样的单路一步神经网络结构搜索 ...
代码地址:https://github.com/DepthAnything/Depth-Anything-V2/tree/main 一、模型改进 将所有标记的真实图像替换为合成图像。 在Depth Anything V2的研究中,研究团队提出了一种创新的方法,即使用完全合成的图像来替代所有带有标签的真实图像,以训练单目...
install.packages("devtools")devtools::install_github("cole-trapnell-lab/cicero-release", ref = "monocle3") #或者从github上下载R包,本地进行安装 install.packages("D:/Program Files/R/R-3.6.2/library/cicero-release-master.z...
|large|1550 M||✓| |turbo|798 M||✓| In December 2022, we[released an improved large model named`large-v2`](https://github.com/openai/whisper/discussions/661), and`large-v3`in November 2023. Additionally, we've added a`turbo`model in September 2024 which is optimized for inference...
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