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README.md

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+# 🧠 Mamba Hypernetwork for LLM Personalization
+
+Mamba Hypernetwork sinh LoRA delta cho LLM tại inference time, cho phép cá nhân hóa tức thì mà không cần retrain.
+
+## Architecture
+- **Mamba**: 1024 dim, 16 state, 4 expand (~12M params)
+- **LoRA**: rank 16, inject vào q_proj + v_proj của 8 layers đầu
+- **LLM**: Llama-3.2-3B-Instruct
+
+## Training
+- **Method**: GRPO (Group Relative Policy Optimization)
+- **Reward Model**: `phammminhhieu/persona-reward-model`
+- **Dataset**: Personachat TrueCased
+
+## Usage
+
+```python
+from mamba_ssm import Mamba
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Load Mamba
+config = json.load(open("config.json"))
+mamba = MambaHypernetwork(config)
+mamba.load_state_dict(torch.load("pytorch_model.bin"))
+mamba.eval()
+
+# Load LLM
+llm = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct")
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-3B-Instruct")
+
+# Sinh delta từ persona
+persona = "I love dogs. I am a photographer."
+deltas = mamba(persona_ids, persona_mask, history_ids, history_mask)
+