---
base_model: Qwen/Qwen3-4B-Instruct-2507
datasets:
- alfworld
- dbbench
language:
- en
license: apache-2.0
library_name: HuggingFace Transformers
pipeline_tag: text-generation
tags:
- agent
- tool-use
- alfworld
- dbbench
---

# Qwen3-4B-Instruct-2507-LoRA-AgentBench

This repository provides a RL'ed model fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using HuggingFace Transformers.

## Training Objective

This model is trained to improve **multi-turn agent task performance**
on ALFWorld (household tasks) and DBBench (database operations).

## Training Configuration
- Base model: Qwen/Qwen3-4B-Instruct-2507
- Method: Agentic Reinforcement Learning
- Max sequence length: 8192
- Learning rate: 1e-06

## Usage

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

base = "fujiki/qw3-4b-v17-gs180"

tokenizer = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(
    base,
    torch_dtype=torch.float16,
    device_map="auto",
)
```

## Sources & Terms (IMPORTANT)

Training data: u-10bei/sft_alfworld_trajectory_dataset_v5, u-10bei/dbbench_sft_dataset_react_v4 and task enviromnents for the Agentic RL of LLM.

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.
