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

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.

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