Beta

Explore
Marketplace
Neural Labs
Chat
Wallet
Docs

Beta

Explore Marketplace Neural Labs Wallet Docs

Build

Manage

My assets Manage wallet Organization

Community

Discord X (Twitter)Telegram

Docs Privacy Policy Terms and Conditions

Proud member of

Proud member of

Docs Cookie Policy

Privacy Policy Terms and Conditions

© 2026 AlphaNeural AI. All rights reserved.

qwen3-4b-structured-output-lora-ma922glow – AI Model by ma922glow | AlphaNeural AI

You can deploy this model and start earning money today!

ma922glow/
qwen3-4b-structured-output-lora-ma922glow

like

0

structured-output

text-generation

daichira/structured-5k-mix-sft

Qwen/Qwen3-4B-Instruct-2507

Views

No views yet

qwen3-4b-structured-output-lora-ma922glow

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: 2
Learning rate: 2e-05
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 = "ma922glow/qwen3-4b-structured-output-lora-ma922glow"

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: CC-BY-4.0. This dataset is licensed under CC-BY-4.0 as it is a purely synthetic collection. Compliance: Users must comply with the CC-BY-4.0 (including copyright notice) and the base model's original terms of use.