corpus.blog
41554 blogs · [ { "id": "01a0ca86-af2f-728b-9534-f4218bb80491", "title": "MiMo-V2.6 Pro Architecture and Training Notes", "url": "https://sebastianraschka.com/blog/2026/mimo-v2-6-pro-architecture-training-notes.html", "published_at": "2026-09-22T13:47:58+00:00" }, { "id": "01a0ca86-af2f-728b-9534-f4218bdc6d42", "title": "It's Easy to Dismiss Jev as Just a Classifier", "url": "https://sebastianraschka.com/blog/2026/jev-classification-generalization.html", "published_at": "2026-09-20T15:17:40+00:00" }, { "id": "01a0ca86-af2f-728b-9534-f4218c4c8320", "title": "Pacing != Pacing Development", "url": "https://sebastianraschka.com/blog/2026/pacing-development.html", "published_at": "2026-09-14T13:27:41+00:00" }, { "id": "01a0ca86-af2f-728b-9534-f4218c5fcb3e", "title": "AI Reasoning Models Course on LinkedIn Learning", "url": "https://sebastianraschka.com/blog/2026/ai-reasoning-models-course.html", "published_at": "2026-09-13T13:11:39+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363dfce3e89", "title": "OpenAI Astra and Looped Transformers", "url": "https://sebastianraschka.com/blog/2026/openai-astra-looped-transformers.html", "published_at": "2026-09-02T08:30:28+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e0244164", "title": "Reasoning Models From Scratch: Code Setup", "url": "https://sebastianraschka.com/blog/2026/reasoning-models-and-agents-from-scratch.html", "published_at": "2026-08-30T13:42:39+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e0dd6a90", "title": "Two Live Book Club Q&As on September 3", "url": "https://sebastianraschka.com/blog/2026/reasoning-model-book-club-q-and-a.html", "published_at": "2026-08-29T11:55:18+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e1572f68", "title": "GLM-5.3-Flash Architecture Notes", "url": "https://sebastianraschka.com/blog/2026/glm-5-3-flash-architecture-notes.html", "published_at": "2026-08-26T10:11:51+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e2a053d3", "title": "How Claude's Text Watermarking Works", "url": "https://sebastianraschka.com/blog/2026/claude-text-watermarking.html", "published_at": "2026-08-15T09:28:41+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e2dece95", "title": "Build a Reasoning Model From Scratch Is Now on Amazon", "url": "https://sebastianraschka.com/blog/2026/build-a-reasoning-model-from-scratch-on-amazon.html", "published_at": "2026-08-12T08:25:44+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e2eaa43e", "title": "Muse Glimmer 30B Architecture Notes", "url": "https://sebastianraschka.com/blog/2026/muse-glimmer-30b-architecture-notes.html", "published_at": "2026-08-11T14:15:07+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e32a5996", "title": "LLMs From Scratch Reaches 100,000 GitHub Stars", "url": "https://sebastianraschka.com/blog/2026/llms-from-scratch-reaches-100000-github-stars.html", "published_at": "2026-08-07T09:40:53+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e3d68cc5", "title": "Kimi K3 Architecture Notes", "url": "https://sebastianraschka.com/blog/2026/kimi-k3-architecture-notes.html", "published_at": "2026-07-28T13:38:20+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e3e351e0", "title": "A Few Notable Open-Weight Models This Week", "url": "https://sebastianraschka.com/blog/2026/notable-open-weight-models-this-week.html", "published_at": "2026-07-26T13:47:44+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e41e13f2", "title": "Correction for Listing 6.5 in Build a Reasoning Model From Scratch", "url": "https://sebastianraschka.com/blog/2026/reasoning-model-listing-6-5-correction.html", "published_at": "2026-07-25T13:18:12+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e551e9b5", "title": "Inkling: A New Open-Weight 975B MoE with a Few Surprises", "url": "https://sebastianraschka.com/blog/2026/inkling-architecture-benchmark-notes.html", "published_at": "2026-07-16T08:50:22+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e5da8101", "title": "200,000 Subscribers", "url": "https://sebastianraschka.com/blog/2026/ahead-of-ai-reached-200000-subscribers.html", "published_at": "2026-07-12T15:04:37+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1363e6375613", "title": "GPT 5.6 Has 72 Possible Configurations. 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And Is DPO Better Than PPO?", "url": "https://magazine.sebastianraschka.com/p/how-good-are-the-latest-open-llms", "published_at": "2024-05-12T06:03:00+00:00" }, { "id": "01a0ca86-af30-71a3-ae94-8f894da0979c", "title": "Using and Finetuning Pretrained Transformers", "url": "https://magazine.sebastianraschka.com/p/using-and-finetuning-pretrained-transformers", "published_at": "2024-04-20T07:00:00+00:00" }, { "id": "01a0ca86-af30-71a3-ae94-8f894e8e1522", "title": "Tips for LLM Pretraining and Evaluating Reward Models", "url": "https://magazine.sebastianraschka.com/p/tips-for-llm-pretraining-and-evaluating-rms", "published_at": "2024-03-31T06:00:00+00:00" }, { "id": "01a087ac-de78-73b1-bc13-dac1b2f0337e", "title": "Linklog | Machine Learning Notebooks", "url": "https://sebastianraschka.com/notebooks/ml-notebooks/", "published_at": "2024-03-05T12:00:00+00:00" }, { "id": "01a0ca86-af30-71a3-ae94-8f894f7ff1b1", "title": "Research Papers in February 2024", "url": "https://magazine.sebastianraschka.com/p/research-papers-in-february-2024", "published_at": "2024-03-03T06:00:00+00:00" }, { "id": "01a0ca86-af30-71a3-ae94-8f894f9af971", "title": "Improving LoRA: Implementing Weight-Decomposed Low-Rank Adaptation (DoRA) from Scratch", "url": "https://magazine.sebastianraschka.com/p/lora-and-dora-from-scratch", "published_at": "2024-02-18T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136401d9c1af", "title": "Optimizing LLMs From a Dataset Perspective", "url": "https://sebastianraschka.com/blog/2023/optimizing-LLMs-dataset-perspective.html", "published_at": "2023-09-15T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136401f6aaff", "title": "The NeurIPS 2023 LLM Efficiency Challenge Starter Guide", "url": "https://sebastianraschka.com/blog/2023/neurips2023-starter-guide.html", "published_at": "2023-08-10T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136402852ba7", "title": "Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorch", "url": "https://sebastianraschka.com/blog/2023/pytorch-memory-optimization.html", "published_at": "2023-07-01T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1364034185d9", "title": "Finetuning Falcon LLMs More Efficiently With LoRA and Adapters", "url": "https://sebastianraschka.com/blog/2023/falcon-finetuning.html", "published_at": "2023-06-14T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136403cf0ead", "title": "Accelerating Large Language Models with Mixed-Precision Techniques", "url": "https://sebastianraschka.com/blog/2023/llm-mixed-precision-copy.html", "published_at": "2023-05-11T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1364042c99bc", "title": "Parameter-Efficient LLM Finetuning With Low-Rank Adaptation (LoRA)", "url": "https://sebastianraschka.com/blog/2023/llm-finetuning-lora.html", "published_at": "2023-04-26T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640447e791", "title": "Understanding Parameter-Efficient Finetuning of Large Language Models: From Prefix Tuning to LLaMA-Adapters", "url": "https://sebastianraschka.com/blog/2023/llm-finetuning-llama-adapter.html", "published_at": "2023-04-12T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136404aba5ac", "title": "Finetuning Large Language Models On A Single GPU Using Gradient Accumulation", "url": "https://lightning.ai/pages/blog/gradient-accumulation/", "published_at": "2023-03-28T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1364053d828e", "title": "Keeping Up With AI Research And News", "url": "https://sebastianraschka.com/blog/2023/keeping-up-with-ai.html", "published_at": "2023-03-23T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136405e69842", "title": "Some Techniques To Make Your PyTorch Models Train (Much) Faster", "url": "https://sebastianraschka.com/blog/2023/pytorch-faster.html", "published_at": "2023-02-23T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136407645d82", "title": "Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratch", "url": "https://sebastianraschka.com/blog/2023/self-attention-from-scratch.html", "published_at": "2023-02-09T08:00:00+00:00" }, { "id": "01a0ca86-af30-71a3-ae94-8f895703ae58", "title": "Understanding and Coding Self-Attention, Multi-Head Attention, Causal Attention, and Cross-Attention in LLMs", "url": "https://magazine.sebastianraschka.com/p/understanding-and-coding-self-attention", "published_at": "2023-02-09T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136407a2efa5", "title": "Understanding Large Language Models -- A Transformative Reading List", "url": "https://sebastianraschka.com/blog/2023/llm-reading-list.html", "published_at": "2023-02-07T08:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136407dafddc", "title": "What Are the Different Approaches for Detecting Content Generated by LLMs Such As ChatGPT? And How Do They Work and Differ?", "url": "https://sebastianraschka.com/blog/2023/detect-ai.html", "published_at": "2023-02-01T09:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136408ac7115", "title": "Comparing Different Automatic Image Augmentation Methods in PyTorch", "url": "https://sebastianraschka.com/blog/2023/data-augmentation-pytorch.html", "published_at": "2023-01-29T09:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136408f54a66", "title": "Curated Resources and Trustworthy Experts: The Key Ingredients for Finding Accurate Answers to Technical Questions in the Future", "url": "https://sebastianraschka.com/blog/2023/chatgpt-dilemma.html", "published_at": "2023-01-16T09:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136409c66829", "title": "Training an XGBoost Classifier Using Cloud GPUs Without Worrying About Infrastructure", "url": "https://sebastianraschka.com/blog/2023/xgboost-gpu.html", "published_at": "2023-01-15T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640a0bd81d", "title": "Open Source Highlights 2022 for Machine Learning & AI", "url": "https://sebastianraschka.com/blog/2023/open-source-highlights-2022.html", "published_at": "2023-01-05T07:00:00+00:00" }, { "id": "01a0ca86-af30-71a3-ae94-8f895b3eb3fe", "title": "Influential Machine Learning Papers Of 2022", "url": "https://magazine.sebastianraschka.com/p/ahead-of-ai-4-a-big-year-for-ai", "published_at": "2023-01-03T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640afe2abe", "title": "Ahead Of AI, And What's Next?", "url": "https://sebastianraschka.com/blog/2022/ahead-of-ai-and-whats-next.html", "published_at": "2022-10-15T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640b38a547", "title": "A Short Chronology Of Deep Learning For Tabular Data", "url": "https://sebastianraschka.com/blog/2022/deep-learning-for-tabular-data.html", "published_at": "2022-07-24T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640b43d39d", "title": "No, We Don't Have to Choose Batch Sizes As Powers Of 2", "url": "https://sebastianraschka.com/blog/2022/batch-size-2.html", "published_at": "2022-07-05T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640bbc366c", "title": "Sharing Deep Learning Research Models with Lightning Part 2: Leveraging the Cloud", "url": "https://sebastianraschka.com/blog/2022/lightning-app-srgan-2.html", "published_at": "2022-06-30T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640bea853d", "title": "Sharing Deep Learning Research Models with Lightning Part 1: Building A Super Resolution App", "url": "https://sebastianraschka.com/blog/2022/lightning-app-srgan-1.html", "published_at": "2022-06-17T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640c9cee87", "title": "Taking Datasets, DataLoaders, and PyTorch’s New DataPipes for a Spin", "url": "https://sebastianraschka.com/blog/2022/datapipes.html", "published_at": "2022-06-12T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640cee62ba", "title": "Running PyTorch on the M1 GPU", "url": "https://sebastianraschka.com/blog/2022/pytorch-m1-gpu.html", "published_at": "2022-05-18T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640d6a5f98", "title": "Creating Confidence Intervals for Machine Learning Classifiers", "url": "https://sebastianraschka.com/blog/2022/confidence-intervals-for-ml.html", "published_at": "2022-04-25T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640e119ec3", "title": "Losses Learned", "url": "https://sebastianraschka.com/blog/2022/losses-learned-part1.html", "published_at": "2022-04-04T15:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640ed0d0bd", "title": "TorchMetrics", "url": "https://sebastianraschka.com/blog/2022/torchmetrics.html", "published_at": "2022-03-24T13:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640ee5bbd7", "title": "Machine Learning with PyTorch and Scikit-Learn", "url": "https://sebastianraschka.com/blog/2022/ml-pytorch-book.html", "published_at": "2022-02-25T07:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13640fde4729", "title": "Introduction to Machine Learning", "url": "https://sebastianraschka.com/blog/2021/ml-course.html", "published_at": "2021-12-29T06:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13641001f824", "title": "Introduction to Deep Learning", "url": "https://sebastianraschka.com/blog/2021/dl-course.html", "published_at": "2021-07-09T06:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1364105c417d", "title": "Datasets for Machine Learning and Deep Learning", "url": "https://sebastianraschka.com/blog/2021/ml-dl-datasets.html", "published_at": "2021-02-11T09:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136411545bcb", "title": "Book Review: Deep Learning With PyTorch", "url": "https://sebastianraschka.com/blog/2021/pytorch-deeplearning-review.html", "published_at": "2021-01-21T09:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-136411cba588", "title": "How I Keep My Projects Organized", "url": "https://sebastianraschka.com/blog/2021/project-management.html", "published_at": "2021-01-03T20:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1364128b6d4f", "title": "Scientific Computing in Python: Introduction to NumPy and Matplotlib", "url": "https://sebastianraschka.com/blog/2020/numpy-intro.html", "published_at": "2020-09-27T17:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13641302d9e0", "title": "Interpretable Machine Learning", "url": "https://sebastianraschka.com/blog/2020/interpretable-ml-1.html", "published_at": "2020-08-26T18:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1364139c6cb1", "title": "Chapter 1: Introduction to Machine Learning and Deep Learning", "url": "https://sebastianraschka.com/blog/2020/intro-to-dl-ch01.html", "published_at": "2020-08-05T21:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-1364144d646b", "title": "Book Review: Architects of Intelligence by Martin Ford", "url": "https://sebastianraschka.com/blog/2020/book-review-1-architects-of-intelligence.html", "published_at": "2020-01-06T13:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13641496709d", "title": "What's New in the 3rd Edition", "url": "https://sebastianraschka.com/blog/2019/whats-new-in-the-3rd-edition.html", "published_at": "2019-12-12T22:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13641540a214", "title": "My First Year at UW-Madison and a Gallery of Awesome Student Projects", "url": "https://sebastianraschka.com/blog/2019/student-gallery-1.html", "published_at": "2019-05-24T22:00:00+00:00" }, { "id": "01a07d5d-9f4f-7055-8ebc-13641627677e", "title": "Model evaluation, model selection, and algorithm selection in machine learning", "url": "https://sebastianraschka.com/blog/2018/model-evaluation-selection-part4.html", "published_at": "2018-11-10T22:00:00+00:00" } ] posts Claim your blog
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Sebastian Raschka

sebastianraschka.com

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
My First Year at UW-Madison and a Gallery of Awesome Student Projectsoriginal ↗
24 May 2019

2018

Model evaluation, model selection, and algorithm selection in machine learningoriginal ↗
10 Nov 2018
Next