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lora_structeval_t_qwen3_4b – AI Model by KeithSimon | AlphaNeural AI

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KeithSimon/
lora_structeval_t_qwen3_4b

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structured-output

text-generation

u-10bei/structured_data_with_cot_dataset_512_v2

Qwen/Qwen3-4B-Instruct-2507

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lora_structeval_t_qwen3_4b

This repository provides a LoRA adapter fine-tuned from Qwen/Qwen3-4B-Instruct-2507 using QLoRA (4-bit).

This repository contains LoRA adapter weights only.

Training Objective

Improve structured output accuracy (JSON / YAML / XML / TOML / CSV).

Training Configuration

Base model: Qwen/Qwen3-4B-Instruct-2507
Max sequence length: 512
Epochs: 1
Learning rate: 1e-06
LoRA: r=64, alpha=128

Usage

python

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

base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "KeithSimon/lora_structeval_t_qwen3_4b"

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

Sources & Terms

Training data: u-10bei/structured_data_with_cot_dataset_512_v2