Popular GitHub Repositories for Bengali Summary Ranking

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

? Scalable embedding, reasoning, ranking for images and sentences with CLIP

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

A free and open source, self hosted Ai based live meeting note taker and minutes summary generator that can completely run in your Local device (Mac OS and windows OS Support added. Working on adding linux support soon)

AI wearables. Put it on, speak, transcribe, automatically

BibiGPT v1 · one-Click AI Summary for Audio/Video & Chat with Learning Content: Bilibili | YouTube | Tweet丨TikTok丨Dropbox丨Google Drive丨Local files | Websites丨Podcasts | Meetings | Lectures, etc. 音视频内容 AI 一键总结 & 对话：哔哩哔哩丨YouTube丨推特丨小红书丨抖音丨快手丨百度网盘丨阿里云盘丨网页丨播客丨会议丨本地文件等 (原 BiliGPT 省流神器 & AI课代表)

?‍? 全世界最好的LLM资料总结（视频生成、Agent、辅助编程、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型） | Summary of the world's best LLM resources.

??? 全世界最好的LLM资料总结（数据处理、模型训练、模型部署、o1 模型、小语言模型、视觉语言模型） | Summary of the world's best LLM resources.

Torchreid: Deep learning person re-identification in PyTorch.

Module for automatic summarization of text documents and HTML pages.

View model summaries in PyTorch!

Learning to Rank in TensorFlow

Collection of popular and reproducible image denoising works.

Multi-Task Deep Neural Networks for Natural Language Understanding

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.

船长关于机器学习、计算机视觉和工程技术的总结和分享

An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"

[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths of multiple open-source LLMs. LLM-Blender cut the weaknesses through ranking and integrate the strengths through fusing generation to enhance the capability of LLMs.

allRank is a framework for training learning-to-rank neural models based on PyTorch.