The Smol Training Playbook
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3.2k
The secrets to building world-class LLMs
🧠 Brain Cache
A curated collection of my favorite AI and ML research papers — one place to find the papers I keep coming back to.
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FineVision: Open Data is All You Need
📝225A new open-source dataset for training VLMs
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physics-intern: an Autonomous Agent for Physics Research
📝49Explore an autonomous AI workflow for physics research
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The Synthetic Data Playbook: Generating Trillions of the Finest Tokens
📝244Explore synthetic data experiments on an interactive bookshelf
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Token-In, Token-Out Done Right
🧩3Interact with a live reaction‑diffusion visual simulation
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Evaluation Guidebook
📝325Explore LLM benchmark scores over time
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The Ultra-Scale Playbook
🌌3.86kThe ultimate guide to training LLM on large GPU Clusters
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Maintain the unmaintainable
📚81Explore the complex relationships between 400+ machine learning models
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FineWeb: decanting the web for the finest text data at scale
🍷1.35kExplore and download the FineWeb web‑scale text dataset
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Porting nanochat to Transformers: an AI modeling history lesson
📝49Learn about ML and Transformers through nanochat
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FinePDFs: Liberating 3T of the finest tokens from PDFs
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Can LLMs Play the Game of Science?
📝28Explore LLM science benchmark scores
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QED-Nano: Teaching a Tiny Model to Prove Hard Theorems
📝74Who needs 1T parameters? Olympiad proofs with a 4B model
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Distilling 100B+ Models 40x Faster with TRL
📝85TRL distillation for 100B+ teachers, 40x faster
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Extracting Signal from the Noise
📝12Explore PR categories with an interactive particle visualization
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The ultimate guide to RL environments: building and scaling them in the LLM era
📝175Building and scaling RL environments for LLM training
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Defeating the trainer-generator precision mismatch in TRL
🎯18Download research PDF (Pro access required)