from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

base = "unsloth/Qwen3-4B-Instruct-2507"
adapter = "your_id/llm2025-qwen3-4b-structured-refined-v4" # Replace with your HF repo ID

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

Sources & License (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.

dkl4/llm2025-qwen3-4b-structured-refined-v4

llm2025-qwen3-4b-structured-refined-v4

Training Objective

Training Configuration

Usage

Sources & License (IMPORTANT)

dkl4/
llm2025-qwen3-4b-structured-refined-v4