metadata
base_model: Qwen/Qwen3-4B-Instruct-2507
datasets:
- u-10bei/structured_data_with_cot_dataset_512_v2
language:
- en
license: apache-2.0
library_name: peft
pipeline_tag: text-generation
tags:
- qlora
- lora
- structured-output
Wave1-HigherLR-Best-JSON-Clean
This repository provides a LoRA adapter fine-tuned from Qwen/Qwen3-4B-Instruct-2507 using SFT with LoRA (r=64, alpha=128, lr=2e-6).
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).
Training Configuration
- Method: SFT with LoRA (r=64, alpha=128, lr=2e-6)
- Base model: Qwen/Qwen3-4B-Instruct-2507
- Dataset: u-10bei/structured_data_with_cot_dataset_512_v2
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch
base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "your_id/your-repo"
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
Dataset License: MIT License. Compliance: Users must comply with the MIT license and the base model's terms.