The dataset used for the training is u-10bei/structured_data_with_cot_dataset_512_v2 with custom modification. After the training data set is downloaded, metadata.format == "toml" is removed.

Usage

python

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

base = "unsloth/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 (IMPORTANT)

Training data: u-10bei/structured_data_with_cot_dataset

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.

sfutenma/lora_structeval_t_qwen3_4b_v260227-105634

lora_structeval_t_qwen3_4b_v260227-105634

Training Objective

Training Configuration

Custom modification of the training dataset

Usage

Sources & Terms (IMPORTANT)

sfutenma/
lora_structeval_t_qwen3_4b_v260227-105634