Text Classification
Transformers
Safetensors
Korean
roberta
DPR
Classification
RAG
text-embeddings-inference
Instructions to use NHNDQ/SelectionModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NHNDQ/SelectionModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NHNDQ/SelectionModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NHNDQ/SelectionModel") model = AutoModelForSequenceClassification.from_pretrained("NHNDQ/SelectionModel") - Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-4.0
language:
- ko
tags:
- DPR
- Classification
- RAG
Model Details
- Model Description: Selection Model
- Developed by: Jisu Kim, TakSung Heo, Minsu Jeong, and Juhwan Lee
- Model Type: Classification
- License: CC-BY-4.0
Dataset
Uses
This model can be used for context extraction.