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🟣 Redis interview questions and answers to help you prepare for your next technical interview in 2025.
Textbook on reinforcement learning from human feedback
Code repository dedicated to experimenting and research with tiny reasoning language model
Notebooks for RAG improving workshop, using HackerNews data
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
AI personal assistant setup for Claude Code
Neural Networks: Zero to Hero
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024
Custom superlinked retriever in langchain
RoleRadar turns free-form requests like “Data Analyst roles in New York with SQL experience.” into structured filters and semantic-vector queries, delivering spot-on matches in seconds.
This is the code repository for the AI project template. The idea of this template is to have a code framework prepared for any AI/ML/MLOps/LLMOps project
Comprehensive system for monitoring changes and fluctuations in Google Ads
A projection-based framework for gradient-free and parallel learning
Kernels & AI inference engine for phone chips
Machine Learning algorithm implementations from scratch.
📄🧠 PageIndex: Document Index for Reasoning-based RAG
This repository contains the JFK Records dataset with ~2.2k declassified documents (~63k pages), cleaned, summarized, and stored in text files
Superlinked is a Python framework for AI Engineers building high-performance search & recommendation applications that combine structured and unstructured data.
VectorHub is a free, open-source learning website for people (software developers to senior ML architects) interested in adding vector retrieval to their ML stack.