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qwen3-4b-structured-mix
NTA2/qwen3-4b-structured-mix
qwen3-4b-structured-mix is a machine learning model from NTA2. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
This is a LoRA adapter fine-tuned on a custom dataset optimized for structured output tasks (JSON/XML). The model was trained using Unsloth and QLoRA on a Tesla T4 GPU.
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Feb 24, 2026
- Updated
- Feb 24, 2026
- SHA
- 1cede992
Base models
Model card
From the Hugging Face model README
Qwen3-4B Structured Output Adapter (Custom Mix)
This is a LoRA adapter fine-tuned on a custom dataset optimized for structured output tasks (JSON/XML). The model was trained using Unsloth and QLoRA on a Tesla T4 GPU.
Training Details
- Base Model: Qwen/Qwen3-4B-Instruct-2507
- Training Data: A filtered and sampled combination (1,500 entries) of:
u-10bei/structured_data_with_cot_dataset_512_v2daichira/structured-hard-sft-4k
- Sequence Length: 1024
- Epochs: 2
- Rank: 64
- Alpha: 128
Usage
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base_model = "Qwen/Qwen3-4B-Instruct-2507"
# Replace with your username/repo
adapter_name = "NTA2/qwen3-4b-structured-mix"
model = AutoModelForCausalLM.from_pretrained(base_model, load_in_4bit=True, device_map="auto")
model = PeftModel.from_pretrained(model, adapter_name)
tokenizer = AutoTokenizer.from_pretrained(base_model)
- Library
- peft
- License
- apache-2.0
- Languages
- en
- Created
- Feb 24, 2026
- Updated
- Feb 24, 2026