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Explore Jev Course – Prefill-Only Inference & Decision Models from Scratch with 80,749 views, 796 likes, and 14 comments. Experience the impact of this video content that has captured audience attention.

Learn how to build high-speed decision-making pipelines for language models using Jev in PyTorch. This comprehensive course covers both encoder and decoder architectures, custom causal attention masking, and KV-cache reuse to bypass slow autoregressive generation. You will also explore fine-tuning techniques, teacher-student distillation, and reinforcement learning methods like GRPO to optimize decision latency and accuracy. Code: https://github.com/vivekkalyanarangan30/how-jev-works ✏️ Course developed by Vivek Kalyanarangan. 📘 Author, Quantization and Fast Inference (Manning) https://hubs.la/Q04ff8F40 ⭐️ Chapters ⭐️ – 0:00:00 Introduction & Course Overview – 0:01:12 What is Jev & LLM Prefill vs. Decode – 0:03:26 Jev Interfaces: Choice, Score, and Boolean – 0:05:30 Prerequisites & Hardware Requirements – 0:07:10 The 3-Phase Roadmap – 0:08:00 Baseline: Vanilla LLM Token-by-Token Decoding – 0:13:00 Stepping Through KV Cache & Autoregressive Loops – 0:21:24 Encoder-Only Architecture for Fast Decisions – 0:25:26 Implementing Encoder-Based Jev in PyTorch – 0:32:00 Question Spans, Mask Tokens & Mean Pooling – 0:36:30 Dot Product Interactions, Linear Heads & Fine-Tuning Approaches – 0:40:42 Decoder-Only Architecture & Context Caching – 0:46:22 Custom Causal Attention Masking for Multi-Question Packing – 0:52:16 Implementing Decoder-Based Jev with KV Cache Re-use – 1:03:52 Extracting Decision Point Logits & Token Probabilities – 1:09:12 Handling Multi-Token Collision Issues – 1:11:15 Training Workflows & Teacher-Student Distillation – 1:12:35 Reinforcement Learning with GRPO & Perturbed Trajectories – 1:16:54 Log Loss, Spherical Scores & Ranked Probability Score (RPS) – 1:21:38 Constructing the Final RLCD Loss Function – 1:23:17 Encoder vs. Decoder: Trade-offs & Architecture Comparison ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp 🎉 Thanks to our Champion and Sponsor supporters: 👾 @omerhattapoglu1158 👾 @goddardtan 👾 @akihayashi6629 👾 @kikilogsin 👾 @anthonycampbell2148 👾 @tobymiller7790 👾 @rajibdassharma497 👾 @CloudVirtualizationEnthusiast 👾 @adilsoncarlosvianacarlos 👾 @martinmacchia1564 👾 @ulisesmoralez4160 👾 @_Oscar_ 👾 @jedi-or-sith2728 👾 @justinhual1290 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

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