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lora-structeval-sft-0205-merged-v2

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 ---
 library_name: transformers
 tags:
 - unsloth
 ---
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 ---
+base_model: Qwen/Qwen3-4B-Instruct-2507
+datasets:
+- u-10bei/dpo-dataset-qwen-cot
+language:
+- en
+license: apache-2.0
 library_name: transformers
+pipeline_tag: text-generation
 tags:
+- dpo
 - unsloth
+- qwen
+- alignment
 ---
+# lora-structeval-sft-0205-merged-v2
+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 a **LoRA adapter** trained with DPO on top of the SFT adapter.
+You need to load the base model and then load this adapter using PEFT.
+## 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**: 1
+- **Learning rate**: 5e-08
+- **Beta**: 0.05
+- **Max sequence length**: 1024
+- **LoRA Config**: r=8, alpha=16 (merged into base)
+## Usage
+Since this is a merged model, you can use it directly with `transformers`.
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+model_id = "lora-structeval-sft-0205-merged-v2"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+# Test inference
+prompt = "Your question here"
+messages = [
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+)
+inputs = tokenizer(
+    text,
+    return_tensors="pt",
+).to("cuda")
+outputs = model.generate(**inputs, max_new_tokens=512)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+## Sources & License (IMPORTANT)
+* **Training Data**: [u-10bei/dpo-dataset-qwen-cot]
+* **License**: MIT License. (As per dataset terms).
+* **Compliance**: Users must follow the original base model's license terms.