Popular GitHub Repositories for Community Datasets

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.

? The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

Proxmox VE Helper-Scripts (Community Edition)

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

DeerFlow is a community-driven Deep Research framework, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.

? Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. ?YC W23

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

pix2code: Generating Code from a Graphical User Interface Screenshot

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Open source annotation tool for machine learning practitioners.

A powerful tool for creating fine-tuning datasets for LLM

Refine high-quality datasets and visual AI models

Techniques for deep learning with satellite & aerial imagery

Community interface for generative AI

Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

Visualizations for machine learning datasets

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

AI Observability & Evaluation