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README.md

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+---
+license: apache-2.0
+pretty_name: Epoch Eli Dataset v3 — S-Tier Coding & Agentic Fine-Tuning Corpus
+language:
+- en
+task_categories:
+- text-generation
+tags:
+- code
+- agentic-coding
+- sharegpt
+- alpaca
+- vision-language
+- qwen
+- epoch
+---
+
+# Epoch Model Suite 1 — Eli Dataset v3
+
+Dataset curated for fine-tuning **Eli** (~3-7B dense coding model, based on Qwen 3-4B).
+
+## Dataset Composition
+
+- **Total S-Tier Samples**: 23,138 pairs
+- **Backend Code (40.5%)**: 9,360 clean pairs across Linux, Kubernetes, Tokio, FastAPI, Hyper, Gin.
+- **Frontend Code & Design Systems (22.9%)**: 5,290 pairs across shadcn/ui, Radix, Mantine, Tailwind, Stripe, Vercel, Apple HIG specs.
+- **Eli Personality (30.2%)**: 6,988 pairs (1,747 unique Q&As oversampled 4x) capturing Eli's casual, direct, fluff-free persona.
+- **Fable-5 Pi Agent Traces (4.3%)**: 1,000 real agentic execution traces (CoT reasoning, Bash/Read/Edit actions).
+- **Agentic Open-Ended Apps (2.2%)**: 500 unique single-file apps and microservices.
+- **Eli-VL Multimodal**: 192 UI WebP screenshot-to-code pairs (`training-data-eli-vl.jsonl`).
+
+## Files Included
+
+- `training-data.jsonl`: Alpaca format (`instruction`, `output`).
+- `training-data-sharegpt.jsonl`: ShareGPT / ChatML format (`conversations`).
+- `training-data-eli-vl.jsonl`: Multimodal screenshot-to-code pairs.
+- `dataset-stats.json`: Automated statistical breakdown.