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

base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "akamei/AK_1ep_1e-5_512_LORAdr_Decay_0215"                      # AK akamei/AK_1ep_1e-5_512_LORAdr_Decay_0215

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.

akamei/AK_1ep_8e-6_512_LORAdr_Decay_WU_0215

Training Objective

Training Configuration

Usage

Sources & Terms (IMPORTANT)

akamei/
AK_1ep_8e-6_512_LORAdr_Decay_WU_0215