初始化项目，由ModelHub XC社区提供模型

Model: Hi-Satoh/adv_sft_dpo_final_2_merged
Source: Original Platform

README.md

@@ -0,0 +1,55 @@
+---
+base_model: Qwen/Qwen3-4B-Instruct-2507
+datasets:
+- Hi-Satoh/test_dpo_dataset
+language:
+- en
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- dpo
+- unsloth
+- qwen
+- alignment
+---
+
+# ＜【課題】ここは自分で記入して下さい＞
+
+This model is a fine-tuned version of **Qwen/Qwen3-4B-Instruct-2507** using **Direct Preference Optimization (DPO)** via the **Unsloth** library.
+
+This repository contains the **full-merged 16-bit weights**. No adapter loading is required.
+
+## Training Objective
+This model has been optimized using DPO to align its responses with preferred outputs, focusing on improving reasoning (Chain-of-Thought) and structured response quality based on the provided preference dataset.
+
+## Training Configuration
+- **Base model**: Qwen/Qwen3-4B-Instruct-2507
+- **Method**: DPO (Direct Preference Optimization)
+- **Epochs**: 2
+- **Learning rate**: 5e-07
+- **Beta**: 0.5
+- **Max sequence length**: 4096
+- **LoRA Config**: r=8, alpha=16 (merged into base)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "Hi-Satoh/adv_sft_dpo_final_2_merged"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+```
+
+## Sources & License (IMPORTANT)
+
+* **Training Data**: [Hi-Satoh/test_dpo_dataset]
+* **License**: MIT License. (As per dataset terms).
+* **Compliance**: Users must follow the original base model's license terms.