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5kmodel – AI Model by shuto22510 | AlphaNeural AI

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shuto22510/
5kmodel

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structured-output

text-generation

daichira/structured-5k-mix-sft

Qwen/Qwen3-4B-Instruct-2507

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qwen3-4b-structured-output-lora_1

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

This repository contains LoRA adapter weights only. The base model must be loaded separately.

Training Objective

This adapter is trained to improve structured output accuracy (JSON / YAML / XML / TOML / CSV).

Loss is applied only to the final assistant output, while intermediate reasoning (Chain-of-Thought) is masked.

Training Configuration

Base model: Qwen/Qwen3-4B-Instruct-2507
Method: QLoRA (4-bit)
Max sequence length: 512
Epochs: 5
Learning rate: 5e-07
LoRA: r=128, alpha=256

Usage

python

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

base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "shuto22510/5kmodel"

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 (IMPORTANT)

Training data: daichira/structured-5k-mix-sft

Dataset License: Creative Commons Attribution (CC-BY-4.0). This dataset is used and can be redistributed under the terms of the CC-BY-4.0 license. Compliance: Users must comply with both the dataset's attribution requirements and the base model's original terms of use.