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

base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "さよかよ/2025LLM"#######################"your_id/your-repo"#########さよかよ/2025LLM#########
                                   ###ハギングフェイスのID/ファイル名
                           ######################################################################
                           ###########################################################################
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_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.

Framework versions

PEFT 0.18.1

Sayokayo/2025LLM_adapter

Training Objective

Training Configuration

Usage

Sources & Terms (IMPORTANT)

Framework versions

Sayokayo/
2025LLM_adapter