We Got Claude to Fine-Tune an Open Source LLM

We Got Claude to Build CUDA Kernels and teach open models!

The NLP Course is becoming the LLM Course

Fine-tune Any LLM from the Hugging Face Hub with Together AI

Open-source LLMs as LangChain Agents

Judge Arena: Benchmarking LLMs as Evaluators

Open LLM Leaderboard: DROP deep dive

StarCoder: A State-of-the-Art LLM for Code

Open-Source Text Generation & LLM Ecosystem at Hugging Face

Jupyter Agents: training LLMs to reason with notebooks

Introducing the Open Leaderboard for Hebrew LLMs!

How to Fine-Tune an LLM: An End-to-End Guide

The article "How to Fine-Tune an LLM: An End-to-End Guide" offers a practical, hands‑on walkthrough for fine‑tuning large language models in real‑world scenarios. It covers the entire process from data preparation to deployment, providing readers with actionable steps to adapt LLMs to specific tasks. The guide is aimed at practitioners looking to implement fine‑tuning in a structured, end‑to‑end manner.

T-LLM Compiler: Trusted LLM-based Code Optimization and Verification Framework

arXiv:2608. 14953v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, and it has since emerged as one of the most fundamental tasks for LLMs to perform; however, at present, LLMs struggle to apply wide-ranging code optimization tasks due to both the complexity of the code and the inability to independently verify the correctness of the transformations.