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  • PYTORCH
  • TRANSFORMERS
  • NLP

Transformer from scratch

Transformer from scratch

A GPT-style language model implemented from scratch in PyTorch: multi-head attention, causal masking and residual blocks written by hand, plus a byte-pair tokenizer and an ablation study. Code at github.com/delcenjo/transformer-from-scratch.

This case study went into production combining art direction, UX/UI design, motion design and creative development in a single pipeline. The goal: make navigating the product feel like a small cinematic experience, not another catalogue.

Tech stack: React, Three.js, GSAP + ScrollTrigger, custom GLSL shaders and Lenis for smooth scroll. 3D models compressed with DRACO and textures in KTX2 to hold 60 fps on mid-range mobile.

Phase 1

Concept

Workshops with the client, visual reference exploration, defining the narrative rhythm and the scroll-driven beats.

Phase 2

Design

Figma mockups with a component system, variable type, an oklch-based palette and a full motion specification.

Phase 3

Build

React + Three.js implementation, asset optimisation, headless CMS integration, cross-device QA and a documented handoff.

Work with JMWEB

Let's build something that reaches production.

It all starts with a conversation. Bring a dataset, a goal or a model that is stuck; I will take care of the rest.

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Crafted with

VS CodeNext.jsReactTypeScriptJavaScriptChromeVS CodeNext.jsReactTypeScriptJavaScriptChrome
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