
Jev Course ā Prefill-Only Inference & Decision Models from Scratch
freeCodeCamp.org, 1 hr 26, 79.1K views, Oct 27, 2026
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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 āļø Course developed by Vivek Kalyanarangan. š Author, Quantization and Fast Inference (Manning) https://hubs.la/Q04ff8F40 āļø Chapters āļø ā 0:00:00 Introduction & Course Overview ā 0:01:12 What is Jev & LLM Prefill vs. Decode ā 0:03:26 Jev Interfaces: Choice, Score, and Boolean ā 0:05:30 Prerequisites & Hardware Requirements ā 0:07:10 The 3-Phase Roadmap ā 0:08:00 Baseline: Vanilla LLM Token-by-Token Decoding ā 0:13:00 Stepping Through KV Cache & Autoregressive Loops ā 0:21:24 Encoder-Only Architecture for Fast Decisions ā 0:25:26 Implementing Encoder-Based Jev in PyTorch ā 0:32:00 Question Spans, Mask Tokens & Mean Pooling ā 0:36:30 Dot Product Interactions, Linear Heads & Fine-Tuning Approaches ā 0:40:42 Decoder-Only Architecture & Context Caching ā 0:46:22 Custom Causal Attention Masking for Multi-Question Packing ā 0:52:16 Implementing Decoder-Based Jev with KV Cache Re-use ā 1:03:52 Extracting Decision Point Logits & Token Probabilities ā 1:09:12 Handling Multi-Token Collision Issues ā 1:11:15 Training Workflows & Teacher-Student Distillation ā 1:12:35 Reinforcement Learning with GRPO & Perturbed Trajectories ā 1:16:54 Log Loss, Spherical Scores & Ranked Probability Score (RPS) ā 1:21:38 Constructing the Final RLCD Loss Function ā 1:23:17 Encoder vs. Decoder: Trade-offs & Architecture Comparison ā¤ļø Support for this channel comes from our friends at Scrimba ā the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp š Thanks to our Champion and Sponsor supporters: š¾ @omerhattapoglu1158 š¾ @goddardtan š¾ @akihayashi6629 š¾ @kikilogsin š¾ @anthonycampbell2148 š¾ @tobymiller7790 š¾ @rajibdassharma497 š¾ @CloudVirtualizationEnthusiast š¾ @adilsoncarlosvianacarlos š¾ @martinmacchia1564 š¾ @ulisesmoralez4160 š¾ @_Oscar_ š¾ @jedi-or-sith2728 š¾ @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