Beta

Explore
Marketplace
Neural Labs
Chat
Wallet
Docs

Beta

Explore Marketplace Neural Labs Wallet Docs

Build

Manage

My assets Manage wallet Organization

Community

Discord X (Twitter)Telegram

Docs Privacy Policy Terms and Conditions

Proud member of

Proud member of

Docs Cookie Policy

Privacy Policy Terms and Conditions

© 2026 AlphaNeural AI. All rights reserved.

shibatake-SFT_2602080302 – AI Model by takeofuture | AlphaNeural AI

You can deploy this model and start earning money today!

takeofuture/
shibatake-SFT_2602080302

like

0

structured-output

text-generation

u-10bei/structured_data_with_cot_dataset_512_v2

Qwen/Qwen3-4B-Instruct-2507

Views

No views yet

qwen3-4b-structured-output-lora-shibatake-v16

This repository provides a LoRA adapter fine-tuned from Qwen/Qwen3-4B-Instruct-2507 using QLoRA (4-bit, Unsloth).

This repository contains LoRA adapter weights only. The base model must be loaded separately.

Training Objective

This adapter is trained to improve structured output accuracy (JSON / YAML / XML / TOML / CSV).

Loss is applied only to the final assistant output, while intermediate reasoning (Chain-of-Thought) is masked.

CoT mask: 1
Learn mode: after_marker
Output markers: Output:,OUTPUT:,Final:,Answer:,Result:,Response:

Training Configuration

Base model: Qwen/Qwen3-4B-Instruct-2507
Method: QLoRA (4-bit, Unsloth)
Max sequence length: 512
Epochs: 5
Learning rate: 1e-06
LoRA: r=64, alpha=128, dropout=0

Usage

pip install -U transformers peft accelerate safetensors

python

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

base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "takeofuture/shibatake-SFT_2602080302"  # ✅ 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: 2026-02-08 03:02:43 UTC