Opensource Awesome List for AI and LLM

Dec 10, 2024

Explore curated open-source lists for AI and LLMs. Discover resources for AI in Libraries, Archives, Museums, and comprehensive collections on Large Language Models (LLMs), including tools, datasets, papers, and tutorials.

Opensource Awesome List for AI and LLM

Awesome Open-Source Lists for AI and LLMs

This article explores two excellent open-source, curated lists focusing on AI and Large Language Models (LLMs):

1. Awesome AI for LAM | awesome-ai4lam

Title: Awesome AI for LAM | awesome-ai4lam URL: https://ai4lam.github.io/awesome-ai4lam/ Description: A curated list of resources, projects, and tools for using Artificial Intelligence in Libraries, Archives, and Museums.

Awesome

This resource provides a comprehensive collection of materials for professionals and enthusiasts in the Libraries, Archives, and Museums (LAM) sector. It includes sections on:

  • Learning Resources: Introductions to AI, Computer Vision, Natural Language Processing, Generative AI, AI in LAM, and other awesome lists. Examples include free courses from MinnaLearn & University of Helsinki and Library Carpentries.
  • Tools and Frameworks: Document analysis, transcription, and labeling; audio and video analysis, transcription, and labeling; indexing and classification; search and retrieval; and applications of Transformers, LLMs, and GPT. Examples include Arkindex, Callico, and Transkribus.
  • Datasets: Datasets available on Hugging Face and elsewhere. Links are provided to perform live searches within Hugging Face for datasets tagged with specific terms.
  • Projects, Initiatives, and Case Studies: Project lists & directories and select individual projects. Examples include BigLAM and the Vatican Manuscripts project.
  • Policies and Recommendations: Statements by organizations and government bodies, surveys of policies and recommendations, and frameworks. Examples include statements from the ACM Technology Policy Council and IFLA.
  • Conferences and Workshops: Upcoming and past conferences and workshops, including the Fantastic Futures conference series.
  • Publications and News Sources: Journals and magazines and news sources.
  • Community and Contributions: Information on how to contribute to the list.
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2. Awesome-LLM: a curated list of Large Language Model

Title: Awesome-LLM: a curated list of Large Language Model URL: https://github.com/Hannibal046/Awesome-LLM Description: A curated list of Large Language Models (LLMs), including papers, frameworks, tools, courses, and applications.

Awesome

This GitHub repository offers a comprehensive collection of resources related to LLMs, categorized into sections such as:

  • Milestone Papers: A chronological list of influential LLM research papers.
  • Other Papers: Links to curated lists of papers on various LLM-related topics (hallucination, instruction tuning, etc.).
  • LLM Leaderboard: Links to various LLM benchmark leaderboards.
  • Open LLM: A list of open-source LLMs, categorized by organization (Meta, Mistral AI, Google, etc.).
  • LLM Data: Links to datasets for LLM training.
  • LLM Evaluation: Tools and frameworks for evaluating LLMs.
  • LLM Training Frameworks: Tools and libraries for training LLMs.
  • LLM Deployment: Tools and platforms for deploying LLMs.
  • LLM Applications: Libraries and frameworks for building LLM applications.
  • LLM Tutorials and Courses: Links to tutorials and courses on LLMs.
  • LLM Books: Books on LLMs.
  • Great thoughts about LLM: Articles and blog posts offering insights into LLMs.
  • Miscellaneous: Other relevant resources.

The repository also includes information on contributing. Note that the content shown here is a snapshot and the actual repository may contain more up-to-date information.

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