I presented a three hour workshop at PyCon US yesterday titled Building software on top of Large Language Models. The goal of the workshop was to give participants everything they …
Mapping the Mind of a Large Language Model
We have identified how millions of concepts are represented inside Claude Sonnet, one of our deployed large language models. This is the first ever detailed look inside a modern, production-grade large language model.
How Large Language Models Actually Work
Build A Large Language Model (From Scratch), Published by Manning, ISBN 978-1633437166
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Maintaining the love for coding in the time of AI
By Alex Band Over the last year, we have seen the profound effects Large Language Models (LLMs) have on our open-source software work at NLnet Labs. These can be grouped into two main areas: community contributions and security reports. Before we dive into this topic, let me first give
sgl-project/sglang
SGLang is a high-performance serving framework for large language models and multimodal models.
Stanford CS336 | Language Modeling from Scratch (Spring 2025 Archive)
Archived course website for Stanford CS336: Language Modeling from Scratch (Spring 2025), including schedule, assignments, logistics, and materials.
Models overview
Claude is a family of state-of-the-art large language models developed by Anthropic. This guide introduces the available models and compares their performance.
How to Make Small Language Models Outperform Large Language Models Using DSPy!
How a 3B Language Model Surpasses an 8B Counterpart with DSPy? “In an era where language models (LMs) are revolutionising countless tasks, their potential is only as powerful as we interpret …
Slop-Machine Future
The arc of large language models is mediocre, and it bends toward “target procurement”.
Scaling Laws Across Model Architectures: A Comparative Analysis of...
The scaling of large language models (LLMs) is a critical research area for the efficiency and effectiveness of model training and deployment. Our work investigates the transferability and...
openbench: Provider-agnostic, open-source evaluation infrastructure for language models
Provider-agnostic, open-source evaluation infrastructure for language models
Training Large Language Models with Interpreter Feedback using WebAssembly
A fast, local, and secure approach to training LLMs for code with WebAssembly and interpreter-based rewards
Beyond Model Collapse: Scaling Up with Synthesized Data Requires...
Large Language Models (LLM) are increasingly trained on data generated by other LLM, either because generated text and images become part of the pre-training corpus, or because synthetized data is...
Jailbreaking Large Language Models: If You Torture the Model Long Enough, It Will Confess!
A Cautionary Tale…
