metadata
base_model: Qwen/Qwen3-4B-Instruct-2507
datasets:
- u-10bei/structured_data_with_cot_dataset_512_v5
language:
- en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- full-finetune
- structured-output
qwen3-4b-structured-output-lora
This repository provides a full fine-tuned model based on Qwen/Qwen3-4B-Instruct-2507 using BF16 full fine-tuning + NEFTune.
This repository contains the complete model weights.
Training Objective
This model is trained to improve structured output accuracy (JSON / YAML / XML / TOML / CSV).
CoT (Chain-of-Thought) is removed from training data during preprocessing.
Training Configuration
- Base model: Qwen/Qwen3-4B-Instruct-2507
- Method: Full fine-tuning (BF16)
- Max sequence length: 2048
- Epochs: 1
- Learning rate: 2e-05
- NEFTune noise alpha: 5.0
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_id = "84basi/lora-10-2"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
Sources & Terms (IMPORTANT)
Training data: u-10bei/structured_data_with_cot_dataset_512_v5
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.