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README.md

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+---
+license: mit
+tags:
+  - lora
+  - fine-tuning
+  - training
+  - identity-replacement
+  - catastrophic-forgetting
+  - progressive-merging
+language:
+  - en
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# 🧟 Body Snatching: Progressive LoRA Merging (PLM)
+
+**Complete model identity replacement using only LoRA-level resources.**
+
+> *"What if catastrophic forgetting is a feature, not a bug?"*
+
+## 🔥 What is this?
+
+**Progressive LoRA Merging (PLM)** is a training methodology that lets you completely replace a model's identity—its personality, reasoning patterns, and learned behaviors—while keeping the architecture intact.
+
+Think of it as **body snatching** for LLMs:
+- The **body** (architecture, tokenizer, attention mechanisms) stays
+- The **soul** (personality, knowledge, behavior) gets replaced
+
+After enough cycles, you don't have "Qwen fine-tuned for X". You have **a completely different model** that happens to use Qwen's skeleton.
+
+## 💡 The Key Insight
+
+Everyone treats **catastrophic forgetting** as a problem to avoid.
+
+We treat it as **the goal**.
+
+## 🔄 How It Works
+
+```
+Cycle 1:  Base Model → Train LoRA → Merge → New Base₁
+Cycle 2:  New Base₁  → Train LoRA → Merge → New Base₂
+...
+Cycle N:  New Base_N = Completely Different Model
+```
+
+Each cycle:
+1. **Train** a small LoRA adapter (~0.1% of parameters)
+2. **Merge** it permanently into the base weights (in BF16, not 4-bit!)
+3. **Fresh LoRA** for the next cycle
+4. **Repeat** until original identity is gone
+
+## 📊 Results
+
+| Cycles | Similarity to Original | Target Identity Match |
+|--------|------------------------|----------------------|
+| 0 | 100% | 0% |
+| 25 | 64% | 41% |
+| 50 | 28% | 73% |
+| 100 | **7%** | **94%** |
+
+After 100 cycles, the model is **93% your data, 7% original**.
+
+## 💰 Resource Comparison
+
+| Method | Hardware | Time | Cost | Result |
+|--------|----------|------|------|--------|
+| Full Fine-tune | 4-8x A100 | Weeks | $10,000+ | Complete replacement |
+| Single LoRA | 1x 24GB | Hours | $10 | Surface adaptation |
+| **PLM (Ours)** | 1x 24GB | Days | $100-500 | **Complete replacement** |
+
+## 🚀 Quick Start
+
+```bash
+pip install torch transformers peft bitsandbytes datasets
+
+python plm.py --base-model Qwen/Qwen3-1.7B --dataset data.jsonl --cycles 100
+```
+
+## 📖 Citation
+
+```bibtex
+@article{drissi2024bodysnatching,
+  title={Body Snatching: Complete Model Identity Replacement via Progressive LoRA Merging},
+  author={Drissi, Ouissam Said},
+  year={2024},
+  url={https://github.com/antibitcoin/progressive-lora-merging}
+}
+```
+
+## 🔗 Links
+
+- **GitHub**: [antibitcoin/progressive-lora-merging](https://github.com/antibitcoin/progressive-lora-merging)
+- **Paper**: [PAPER.md](https://github.com/antibitcoin/progressive-lora-merging/blob/main/PAPER.md)
+- **Related Work**: [ASRL Paper (IJSET 2025)](https://www.ijset.in/wp-content/uploads/IJSET_V13_issue5_102.pdf)
+
+## 👤 Author
+
+**Ouissam Said Drissi**
+- Email: wissam.idrissi@gmail.com
+- Independent Researcher, Morocco
+
+---
+
+*"You're not fine-tuning a model. You're growing a new one inside its skeleton."*