README.md

---
base_model: Qwen/Qwen3-4B-Instruct-2507
datasets:
- u-10bei/dbbench_sft_dataset_react
- u-10bei/dbbench_sft_dataset_react_v2
- u-10bei/dbbench_sft_dataset_react_v3
- u-10bei/dbbench_sft_dataset_react_v4
language:
- en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- unsloth
- agent
- tool-use
- dbbench
---

# Qwen3-4B-Agent-DBBench-Specialist

This repository provides a **merged full-parameter model** (bfloat16) fine-tuned from **Qwen/Qwen3-4B-Instruct-2507**. 

Instead of a standalone LoRA adapter, this model has been created by merging LoRA weights back into the base model using **Unsloth's `merge_and_unload`** method. This ensures high-speed inference and easy deployment.

## Training Objective
This model is specialized for **DBBench trajectory tasks**, trained to handle multi-turn environment observations and action selections.

## Training Configuration

- **Base model**: Qwen/Qwen3-4B-Instruct-2507
- **Format**: Merged Full Weights (bfloat16)
- **Method**: LoRA fine-tuning (Merged via Unsloth `merge_and_unload`)
- **Max sequence length**: 4096
- **Steps**: 500
- **Learning rate**: 5e-07
- **LoRA Parameters during training**: r=64, alpha=128
- **Platform**: Trained with Unsloth

## Usage

Since this is a merged model, you can load it directly like any other Qwen3 model:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "moushi21/agent-bench-dbbench-merged4"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)
```

## Sources & Terms (IMPORTANT)

Training data:
- u-10bei/dbbench_sft_dataset_react
- u-10bei/dbbench_sft_dataset_react_v2
- u-10bei/dbbench_sft_dataset_react_v3
- u-10bei/dbbench_sft_dataset_react_v4

Dataset License: MIT License. This dataset is used and distributed under the terms of the MIT License.
Compliance: Users must comply with the MIT license (including copyright notice) and the base model's original terms of use.