koelectra base v3 finetuned korquad

Providermonologg
Categoryquestion-answering
LicenseApache-2.0
Downloads249.5K
Stars0

Overview

The koelectra-base-v3-korquad model is a specialized encoder-based transformer optimized for Korean extractive question answering. By leveraging the ELECTRA architecture—which replaces traditional masked language modeling with a more efficient discriminative objective—this model achieves a stronger understanding of Korean linguistic nuances compared to standard BERT variants. It has been specifically fine-tuned on the KorQuAD dataset, making it an ideal choice for developers building RAG (Retrieval-Augmented Generation) pipelines or local knowledge-base search tools where precise span extraction from a given context is required. It integrates seamlessly via the Hugging Face Transformers library, providing a lightweight, high-performance alternative to larger LLMs for targeted QA tasks.

Highlights

  • Optimized for Korean extractive question answering tasks
  • Fine-tuned on the comprehensive KorQuAD benchmark
  • Efficient ELECTRA architecture reduces computational overhead
  • Seamless integration with Hugging Face Transformers library
  • Apache-2.0 license allows flexible commercial deployment

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("monologg/koelectra-base-v3-finetuned-korquad")
tokenizer = AutoTokenizer.from_pretrained("monologg/koelectra-base-v3-finetuned-korquad")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance 
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository 
huggingface-cli download monologg/koelectra-base-v3-finetuned-korquad

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir) 
huggingface-cli download monologg/koelectra-base-v3-finetuned-korquad config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download 
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('monologg/koelectra-base-v3-finetuned-korquad')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://huggingface.co/monologg/koelectra-base-v3-finetuned-korquad

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/monologg/koelectra-base-v3-finetuned-korquad

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers 
pip install -U transformers torch

Load the model and run inference

Load the model and run inference 
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('monologg/koelectra-base-v3-finetuned-korquad')
tokenizer = AutoTokenizer.from_pretrained('monologg/koelectra-base-v3-finetuned-korquad')
View official source
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