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qwen3-4b-struct-exp30 – AI Model by curio184 | AlphaNeural AI

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curio184/
qwen3-4b-struct-exp30

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text-generation

structured-output

u-10bei/structured_data_with_cot_dataset_512_v2

Qwen/Qwen3-4B-Instruct-2507

text-generation-inference

endpoints_compatible

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qwen3-4b-struct-exp30

This model is a fine-tuned version of Qwen/Qwen3-4B-Instruct-2507 using QLoRA (4-bit, Unsloth).

This repository contains the full merged 16-bit weights. No adapter loading is required.

Training Objective

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

Training Configuration

Base model: Qwen/Qwen3-4B-Instruct-2507
Dataset: u-10bei/structured_data_with_cot_dataset_512_v2
Method: QLoRA (4-bit)
Max sequence length: 512
Epochs: 3
Learning rate: 1e-06
LoRA: r=64, alpha=128

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "curio184/qwen3-4b-struct-exp30"

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

Sources & Terms (IMPORTANT)

Training data: u-10bei/structured_data_with_cot_dataset_512_v2

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.