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README.md

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+---
+license: mit
+language: en
+datasets:
+- roneneldan/TinyStoriesInstruct
+base_model: singhpratech/tiny-storyteller
+tags:
+- tiny
+- instruction-tuning
+- chat-template
+- prompt-masking
+- pytorch
+- educational
+- text-generation
+- emc2
+---
+# e=mc² Lesson 05: Instruction tuning from scratch
+
+Lesson page: https://theaivibe.org/emc2/instruction-tuning-from-scratch-tiny-storyteller
+
+Lesson 05 of e=mc², a learn-by-building course by Prateek Singh. It takes `tiny-storyteller-v2`
+(Lesson 04, repo `singhpratech/emc2-lesson-04-fine-tune`) and teaches it to follow a request, with two new
+special tokens, a chat template and prompt masking.
+
+## Contents
+- `lesson_05.ipynb`: the lesson, unexecuted (Colab T4, Apple-silicon Mac or CPU).
+- `RESULTS.md`: every number from the run on 2026-10-11 (Apple M4 Max).
+- `tiny-storyteller-instruct/`: the instruction-tuned model (vocab 4,098) with `chat_template.json`.
+- `pairs/`: the instruction pairs as JSONL (`train`, `heldout`, `test50`, `familiar50`, `crossworld20`).
+- `story_pairs.py`: builds instruction pairs from the Momo and Zuri story generators.
+
+## Result (string match: character AND place in the generated story, 50 held-out instructions)
+| | both | character | place |
+|---|---|---|---|
+| before tuning | 12% | 68% | 14% |
+| after 500 steps | 44% | 100% | 44% |
+
+Held-out instructions ask for character + scene + place combinations that never appear together in training.
+On 50 familiar combinations the same model scores 86%; across the two characters' worlds, 5% of 20.
+
+## Template
+`<|endoftext|><|instruction|>{instruction}<|story|>{story}<|endoftext|>` - generate after `<|story|>`
+until `<|endoftext|>`. Model class: Lesson 01's `GPT`, unchanged (in the notebook).
+
+Licences: code and weights MIT. Pairs derived from TinyStories-Instruct (CDLA-Sharing-1.0) keep that licence;
+generator pairs are MIT.