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CodeZen

CodeZen

一个专注中文区的 GitHub 项目发现

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colpali

The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.

colpali colqwen2 colsmol information-retrieval retrieval-augmented-generation
star2.3k
Python
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o-lib

开源图书Olib客户端源代码 由于代码内部有冗余包,因此目前没有提供环境文件requirements.txt,需要手动进行安装。 你可以在BiliBili找到我. 也可以关注我的公众号【拾壹0x7f】。

star2.3k
Python
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MimicMotion

High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance

diffusion-models video-generation
star2.5k
Python
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mast3r

Grounding Image Matching in 3D with MASt3R

star2.6k
Python
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datachain

ETL, Analytics, Versioning for Unstructured Data

ai cv data-analytics data-wrangling embeddings
star2.7k
Python
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AI-Youtube-Shorts-Generator

A python tool that uses GPT-4, FFmpeg, and OpenCV to automatically analyze videos, extract the most interesting sections, and crop them for an improved viewing experience.

ai-video-generator artificial-intelligence image-to-video image-to-video-generation shorts
star2.7k
Python
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MoA

Together Mixture-Of-Agents (MoA) – 65.1% on AlpacaEval with OSS models

star2.8k
Python
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textgrad

TextGrad: Automatic ''Differentiation'' via Text -- using large language models to backpropagate textual gradients. Published in Nature.

ai-optimization compound-systems large-language-models prompt-optimization textual-gradients
star3.1k
Python
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unitycatalog

Open, Multi-modal Catalog for Data & AI

star3.2k
Python
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ai-agents-masterclass

Follow along with my AI Agents Masterclass videos! All of the code I create and use in this series on YouTube will be here for you to use and even build on top of!

star3.2k
Python
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LazyLLM

LazyLLM: A Low-code Development Tool For Building Multi-agent LLMs Applications. 中文README.CN.md | ENREADME.md What is LazyLLM? LazyLLM is a low-code development tool for building **multi-agent** large language model applications. It assists developers in creating complex AI applications at

agents ai-agent data deep-learning documentation-tool
star3.2k
Python
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gptpdf

gptpdf 使用视觉大语言模型(如 GPT-4o)将 PDF 解析为 markdown。 我们的方法非常简单只有293行代码,但几乎可以完美地解析排版、数学公式、表格、图片、图表等。 每页平均价格:0.013 美元 pdfgpt-uihttps://github.com/daodao97/gptpdf-ui 是一个基于 gptpdf 的可视化工具。 处理流程 1. 使用 PyMuPDF 库,对 PDF 进行解析出所有非文本区域,并做好标记,比如: 2. 使用视觉大模型(如 GPT-4o)进行解析,得到 markdown 文件。 样例 有关 PDF,请参阅 ex

star3.5k
Python