base_model, datasets, language, license, library_name, pipeline_tag, tags

base_model	datasets	language	license	library_name	pipeline_tag	tags
Qwen/Qwen3-4B-Instruct-2507	u-10bei/sft_alfworld_trajectory_dataset_v5 u-10bei/sft_alfworld_trajectory_dataset_v4 u-10bei/dbbench_sft_dataset_react_v4 u-10bei/dbbench_sft_dataset_react_v3	en	apache-2.0	transformers	text-generation	agent tool-use alfworld dbbench

qwen3-4b-agent-full-v3

This repository provides a fully fine-tuned model based on Qwen/Qwen3-4B-Instruct-2507.

Because this model underwent full parameter fine-tuning, this repository contains the full model weights. You can load it directly without needing to merge it with the base model.

Training Objective

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

Loss is applied to all assistant turns in the multi-turn trajectory, enabling the model to learn environment observation, action selection, tool use, and recovery from errors.

Training Configuration

• Base model: Qwen/Qwen3-4B-Instruct-2507
• Method: full
• Max sequence length: 4096
• Epochs: 2
• Learning rate: 2e-06

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

base = "Qwen/Qwen3-4B-Instruct-2507"

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_v4, u-10bei/sft_alfworld_trajectory_dataset_v5, u-10bei/dbbench_sft_dataset_react_v4, u-10bei/dbbench_sft_dataset_react_v3

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.