Large Language Models (LLM)

• ChatGPT Is An Extra-Ordinary Python Programmer
• StartChat Playground by Hugging Face
• What is ChatGPT doing and why does it work
• GPT in 60 Lines of NumPy
• privateGPT
• Pushing Prompt Engineering to the Limit
• How Foundation Model Providers Comply with the Draft EU AI Act
• A Gentle Introduction to LLM APIs
• All You Need to Know to Build Your First LLM App
• Mastering Prompt Engineering
• How to Run LLMs Locally
• LangChain: Building applications with LLMs through composability
• DeclarAI: turning Python code into production-ready LLM tasks
• Open Source LLMs To Power A LLM Application
• Large language models, explained with a minimum of math and jargon
• Inside GPT: Understanding the text generation
• Llama 2: Open Foundation and Fine-Tuned Chat Models
• Understand how BERT constructs state-of-the-art embeddings
• codellama
• NLP tasks via LLM
• From encoding to embeddings
• Large Language Models: Sentence-BERT
• Methods For Improving Your Large Language Model
• Vector Databases and How to Use Them to Augment LLM
• Large Language Models: RoBERTa, a Robustly Optimized BERT Approach
• DeepEval: Unit Testing for LLMs
• Attention Sinks in LLMs for endless fluency
• Generative AI exists because of the transformer: this is how it works
• OpenLLM Leaderboard
• All you need to know to Develop using Large Language Models
• LMQL: a programming language for large language models
• GPT-Engineer
• Chatbot Arena: Benchmarking LLMs in the Wild
• magentic: easily integrate Large Language Models into your Python code
• Hard Truths About Generative AI for Technology Leaders
• AlphaCodium: From Prompt Engineering to Flow Engineering
• Cheshire-Cat: Production ready AI assistant framework
• OLMo: a State-of-the-Art, Truly Open LLM and Framework
• Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
• Cohere For AI Launches Aya: an LLM Covering More Than 100 Languages
• A non-exhaustive but essential list of key papers that underpins text-to-video Deep Generative model like SORA
• Do large language models understand the world?
• A Visual Guide to Mamba and State Space Models
• Gemma: una nuova famiglia di modelli aperti
• DSPy: the framework for programming - not prompting! - foundation models
• Text Embeddings: Comprehensive Guide
• Developers with AI assistants need to follow the pair programming model
• LLM Evaluation
• A programming framework for agentic AI
• Gemma 2 optimized for your local machine
• GraphRAG: a modular graph-based Retrieval-Augmented Generation (RAG) system
• Explaining generative language models to (almost) anyone
• Auditing the Ask Astro LLM Q&A app
• The Rise of the LLM OS: From AIOS to MemGPT and beyond
• A Visual Guide to Quantization
• Unsloth: Finetune Llama 3.1, Mistral, Phi and Gemma
• Open WebUI: user-friendly WebUI for LLMs
• LangDrive: train LLMs on private data
• llmware: unified framework for building enterprise RAG pipelines with small, specialized models
• giskard: Open-Source Evaluation & Testing for LLMs and ML models
• talkd/dialog: RAG LLM Ops App for easy deployment and testing
• LLM sampling
• AI models collapse when trained on recursively generated data
• Trace: AutoDiff for AI Systems and LLM Agents
• Will We Run Out of Data? Limits of LLM Scaling Based on Human-Generated Data
• LitGPT: 2high-performance LLMs with recipes to pretrain, finetune and deploy at scale
• How to build a basic LLM GPT model from Scratch in Python
• guidance: a guidance language for controlling large language models