muratcankoylan/book-training

最近记录的来源活动: 2025年12月27日 10:05

SkillsMP 收录数据更新: 2026年11月2日 18:02

已收集 skills: 4

GitHub 星标: 36
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# Book Training: Style Transfer via SFT A complete pipeline for training language models to write in a specific author's style using Supervised Fine-Tuning (SFT) with LoRA. ## Project Overview This repository demonstrates how to: 1. Extract and segment text from EPUB books 2. Generate diverse instruction-response pairs using LLMs 3. Train a small model (Qwen3-8B-Base) with LoRA 4. Validate genuine style transfer vs. memorization ## Results Trained on Gertrude Stein's "Three Lives" (1909): | Metric | Value | |--------|-------| | Training Examples | 591 | | Final Test Loss | 213 (from 7,584) | | Loss Reduction | 97% | | Training Time | ~15 min | | AI Detector Score | ~50-70% Human (Pangram) | The model applies Stein's style to modern scenarios not in training data, confirming style transfer rather than memorization. ## Repository Structure ``` ├── skills/book-sft-pipeline/ # Reusable skill for AI agents │ ├── SKILL.md # Main skill definition │ ├── references/ # Segmentation, training docs │ ├── scripts/ # Example pipeline code │ └── examples/gertrude-stein/ # Complete case study ├── src/ │ ├── pipeline.ts # Dataset generation pipeline │ └── train-tinker.ts # Tinker training setup ├── train_tinker.py # LoRA training script ├── chat.py # Interactive model testing ├── test_style_transfer.py # Style validation tests ├── hf-dataset/ # HuggingFace dataset files │ ├── train.jsonl # 591 training examples │ ├── test.jsonl # 49 test examples │ └── README.md # Dataset card └── three-lives-sft-dataset.jsonl # Full generated dataset ``` ## Quick Start ### 1. Generate Dataset ```bash npm install npx tsx src/pipeline.ts ``` ### 2. Train with Tinker ```bash pip install tinker python-dotenv python train_tinker.py ``` ### 3. Test the Model ```bash python chat.py ``` ## Dataset Available on HuggingFace: [MuratcanKoylan/gertrude-stein-style-sft](https://huggingface.co/datasets/MuratcanKoylan/gertrude-stein-style-sft) ```python from datasets import load_dataset dataset = load_dataset("MuratcanKoylan/gertrude-stein-style-sft") ``` ## Key Techniques ### Prompt Diversity 15 prompt templates × 5 system prompts = 75 unique combinations per chunk. Prevents overfitting to specific phrasings. ### Fine-Grained Segmentation 150-400 word chunks with overlap. Smaller chunks capture more stylistic patterns. ### Modern Scenario Testing Validate style transfer by prompting about topics the author never wrote about (real estate offices, smartphones, etc.). ## Skills for AI Agents The `/skills/book-sft-pipeline` folder contains a complete skill definition that enables AI agents to replicate this pipeline for any book: ``` skills/book-sft-pipeline/ ├── SKILL.md # Agent-readable instructions ├── references/ # Technical documentation ├── scripts/ # Example implementations └── examples/ # Case studies with results ``` ## Sample Output **Prompt**: Write about a tech startup founder in the style of Gertrude Stein. **Output**: > She was always working, always she was working on her startup. The investors they would come and they would go and she would talk to them about the product. She was a good founder, always she was a good founder. She had this way of explaining things, simple and direct, and the investors they would listen. ## License MIT Source text "Three Lives" by Gertrude Stein (1909) is in the public domain.

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book-sft-pipeline

数据科学家

End-to-end system for creating supervised fine-tuning datasets from books and training style-transfer models. Covers text extraction, intelligent segmentation, synthetic instruction generation, Tinker-compatible output, LoRA training, and validation.

原文语言：英语

2025-12-27

context-compression

计算机与信息研究科学家

Design and evaluate context compression strategies for long-running agent sessions. Use when agents exhaust memory, need to summarize conversation history, or when optimizing tokens-per-task rather than tokens-per-request.

原文语言：英语

2025-12-27

evaluation

软件开发工程师

Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.

原文语言：英语

2025-12-27

tool-design

软件开发工程师

Design tools that agents can use effectively, including when to reduce tool complexity. Use when creating, optimizing, or reducing agent tool sets.

原文语言：英语

2025-12-27

已展示 4 / 4 个已收集 Skill。