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

base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "takeofuture/shibatake-SFT_2602032349"  # ✅ this repo id

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

Sources & Terms (IMPORTANT)

Training data: u-10bei/structured_data_with_cot_dataset_512_v2
Dataset License: MIT License
Compliance: Users must comply with the dataset license (including copyright notice) and the base model's original terms of use.

Last updated: 2026-02-03 23:54:29 UTC

takeofuture/shibatake-SFT_2602032354

qwen3-4b-structured-output-lora-shibatake-v1

Training Objective

Training Configuration

Usage

Sources & Terms (IMPORTANT)

takeofuture/
shibatake-SFT_2602032354