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qwen3-4b-agentbench-opd-adapter-v2-sample – AI Model by Kaito-F | AlphaNeural AI

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Kaito-F/
qwen3-4b-agentbench-opd-adapter-v2-sample

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knowledge-distillation

text-generation

u-10bei/sft_alfworld_trajectory_dataset_v5

u-10bei/dbbench_sft_dataset_react_v4

Qwen/Qwen3-4B-Instruct-2507

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Qwen3-4B AgentBench LoRA (SFT + OPD)

This LoRA adapter was trained in two stages:

SFT (Supervised Fine-Tuning) on agent trajectory data
OPD (On-Policy Distillation) from Qwen/Qwen3-30B-A3B-Instruct-2507

Training Configuration

Stage 1: SFT

Base model: Qwen/Qwen3-4B-Instruct-2507
Dataset: ALFWorld trajectories

Stage 2: OPD

Teacher model: Qwen/Qwen3-30B-A3B-Instruct-2507
Dataset: ALFWorld + DBBench (combined)
Steps: 100
Learning rate: 1e-05

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "Kaito-F/qwen3-4b-agentbench-opd-adapter-v2-sample"

tokenizer = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, adapter)