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Sebastian Raschka

sebastianraschka.com

2026

Language Models for Text Classification: From Bag-of-Words to Jevoriginal ↗
29 Sept 2026
Focusing on Post-Trainingoriginal ↗
27 Sept 2026
MiMo-V2.6 Pro Architecture and Training Notesoriginal ↗
22 Sept 2026
It's Easy to Dismiss Jev as Just a Classifieroriginal ↗
20 Sept 2026
Pacing != Pacing Developmentoriginal ↗
14 Sept 2026
AI Reasoning Models Course on LinkedIn Learningoriginal ↗
13 Sept 2026
OpenAI Astra and Looped Transformersoriginal ↗
2 Sept 2026
Reasoning Models From Scratch: Code Setuporiginal ↗
30 Aug 2026
Two Live Book Club Q&As on September 3original ↗
29 Aug 2026
GLM-5.3-Flash Architecture Notesoriginal ↗
26 Aug 2026
How Claude's Text Watermarking Worksoriginal ↗
15 Aug 2026
Build a Reasoning Model From Scratch Is Now on Amazonoriginal ↗
12 Aug 2026
Muse Glimmer 30B Architecture Notesoriginal ↗
11 Aug 2026
LLMs From Scratch Reaches 100,000 GitHub Starsoriginal ↗
7 Aug 2026
Kimi K3 Architecture Notesoriginal ↗
28 Jul 2026
A Few Notable Open-Weight Models This Weekoriginal ↗
26 Jul 2026
Correction for Listing 6.5 in Build a Reasoning Model From Scratchoriginal ↗
25 Jul 2026
Inkling: A New Open-Weight 975B MoE with a Few Surprisesoriginal ↗
16 Jul 2026
200,000 Subscribersoriginal ↗
12 Jul 2026
GPT 5.6 Has 72 Possible Configurations. What's A Good Default?original ↗
9 Jul 2026
Build a Reasoning Model From Scratch Is Outoriginal ↗
30 Jun 2026
Using Local Coding Agentsoriginal ↗
29 Jun 2026
Local Open-Weight LLMs in Coding Harnessesoriginal ↗
26 Jun 2026
GLM-5.2 and IndexShare for Long-Context Sparse Attentionoriginal ↗
18 Jun 2026
VibeThinker-3B and the Strength of Post-Trainingoriginal ↗
17 Jun 2026
North Mini Code and Agentic Coding Benchmarksoriginal ↗
12 Jun 2026
Nemotron 3 Ultra and Latent MoE Scalingoriginal ↗
4 Jun 2026
MiniMax M2 Technical Report Notesoriginal ↗
27 May 2026
DeepSeek Sparse Attention From Scratchoriginal ↗
23 May 2026
Implementing LLM Architectures From Scratchoriginal ↗
14 May 2026
Gemma 4 Architecture and Benchmark Notesoriginal ↗
2 Apr 2026
LLM Architecture Gallery Diff Tooloriginal ↗
26 Mar 2026
Inside the LLM Architecture Galleryoriginal ↗
14 Mar 2026
Nemotron 3 Super Throughput Notesoriginal ↗
12 Mar 2026
State of AI 2026 with Sebastian Raschka, Nathan Lambert, and Lex Fridmanoriginal ↗
1 Feb 2026

2025

From Random Forests to RLVR: A Short History of ML/AI Hello Worldsoriginal ↗
8 Dec 2025
Recommendations for Getting the Most Out of a Technical Bookoriginal ↗
12 Nov 2025
DGX Spark and Mac Mini for Local PyTorch Developmentoriginal ↗
29 Oct 2025
Understanding and Coding the KV Cache in LLMs from Scratchoriginal ↗
17 Jun 2025
Coding LLMs from the Ground Up: A Complete Courseoriginal ↗
10 May 2025
The State of Reinforcement Learning for LLM Reasoningoriginal ↗
19 Apr 2025
First Look at Reasoning From Scratch: Chapter 1original ↗
29 Mar 2025
Inference-Time Compute Scaling Methods to Improve Reasoning Modelsoriginal ↗
8 Mar 2025
Understanding Reasoning LLMsoriginal ↗
5 Feb 2025
Noteworthy LLM Research Papers of 2024original ↗
23 Jan 2025
Implementing A Byte Pair Encoding (BPE) Tokenizer From Scratchoriginal ↗
17 Jan 2025

2024

LLM Research Papers: The 2024 Listoriginal ↗
29 Dec 2024
Understanding Multimodal LLMsoriginal ↗
3 Nov 2024
Building A GPT-Style LLM Classifier From Scratchoriginal ↗
21 Sept 2024
Building LLMs from the Ground Up: A 3-hour Coding Workshoporiginal ↗
1 Sept 2024
New LLM Pre-training and Post-training Paradigmsoriginal ↗
17 Aug 2024
Instruction Pretraining LLMsoriginal ↗
20 Jul 2024
Developing an LLM: Building, Training, Finetuningoriginal ↗
2 Jun 2024
LLM Research Insights: Instruction Masking and New LoRA Finetuning Experiments?original ↗
2 Jun 2024
How Good Are the Latest Open LLMs? And Is DPO Better Than PPO?original ↗
12 May 2024
Using and Finetuning Pretrained Transformersoriginal ↗
20 Apr 2024
Tips for LLM Pretraining and Evaluating Reward Modelsoriginal ↗
31 Mar 2024
Linklog | Machine Learning Notebooksoriginal ↗
5 Mar 2024
Research Papers in February 2024original ↗
3 Mar 2024
Improving LoRA: Implementing Weight-Decomposed Low-Rank Adaptation (DoRA) from Scratchoriginal ↗
18 Feb 2024

2023

Optimizing LLMs From a Dataset Perspectiveoriginal ↗
15 Sept 2023
The NeurIPS 2023 LLM Efficiency Challenge Starter Guideoriginal ↗
10 Aug 2023
Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorchoriginal ↗
1 Jul 2023
Finetuning Falcon LLMs More Efficiently With LoRA and Adaptersoriginal ↗
14 Jun 2023
Accelerating Large Language Models with Mixed-Precision Techniquesoriginal ↗
11 May 2023
Parameter-Efficient LLM Finetuning With Low-Rank Adaptation (LoRA)original ↗
26 Apr 2023
Understanding Parameter-Efficient Finetuning of Large Language Models: From Prefix Tuning to LLaMA-Adaptersoriginal ↗
12 Apr 2023
Finetuning Large Language Models On A Single GPU Using Gradient Accumulationoriginal ↗
28 Mar 2023
Keeping Up With AI Research And Newsoriginal ↗
23 Mar 2023
Some Techniques To Make Your PyTorch Models Train (Much) Fasteroriginal ↗
23 Feb 2023
Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratchoriginal ↗
9 Feb 2023
Understanding and Coding Self-Attention, Multi-Head Attention, Causal Attention, and Cross-Attention in LLMsoriginal ↗
9 Feb 2023
Understanding Large Language Models -- A Transformative Reading Listoriginal ↗
7 Feb 2023
What Are the Different Approaches for Detecting Content Generated by LLMs Such As ChatGPT? And How Do They Work and Differ?original ↗
1 Feb 2023
Comparing Different Automatic Image Augmentation Methods in PyTorchoriginal ↗
29 Jan 2023
Curated Resources and Trustworthy Experts: The Key Ingredients for Finding Accurate Answers to Technical Questions in the Futureoriginal ↗
16 Jan 2023
Training an XGBoost Classifier Using Cloud GPUs Without Worrying About Infrastructureoriginal ↗
15 Jan 2023
Open Source Highlights 2022 for Machine Learning & AIoriginal ↗
5 Jan 2023
Influential Machine Learning Papers Of 2022original ↗
3 Jan 2023

2022

Ahead Of AI, And What's Next?original ↗
15 Oct 2022
A Short Chronology Of Deep Learning For Tabular Dataoriginal ↗
24 Jul 2022
No, We Don't Have to Choose Batch Sizes As Powers Of 2original ↗
5 Jul 2022
Sharing Deep Learning Research Models with Lightning Part 2: Leveraging the Cloudoriginal ↗
30 Jun 2022
Sharing Deep Learning Research Models with Lightning Part 1: Building A Super Resolution Apporiginal ↗
17 Jun 2022
Taking Datasets, DataLoaders, and PyTorch’s New DataPipes for a Spinoriginal ↗
12 Jun 2022
Running PyTorch on the M1 GPUoriginal ↗
18 May 2022
Creating Confidence Intervals for Machine Learning Classifiersoriginal ↗
25 Apr 2022
Losses Learnedoriginal ↗
4 Apr 2022
TorchMetricsoriginal ↗
24 Mar 2022
Machine Learning with PyTorch and Scikit-Learnoriginal ↗
25 Feb 2022

2021

Introduction to Machine Learningoriginal ↗
29 Dec 2021
Introduction to Deep Learningoriginal ↗
9 Jul 2021
Datasets for Machine Learning and Deep Learningoriginal ↗
11 Feb 2021
Book Review: Deep Learning With PyTorchoriginal ↗
21 Jan 2021
How I Keep My Projects Organizedoriginal ↗
3 Jan 2021

2020

Scientific Computing in Python: Introduction to NumPy and Matplotliboriginal ↗
27 Sept 2020
Interpretable Machine Learningoriginal ↗
26 Aug 2020
Chapter 1: Introduction to Machine Learning and Deep Learningoriginal ↗
5 Aug 2020
Book Review: Architects of Intelligence by Martin Fordoriginal ↗
6 Jan 2020

2019

What's New in the 3rd Editionoriginal ↗
12 Dec 2019
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