Edit model card

πŸ§‘πŸ»β€πŸ’» KLUE RoBERTa Large

  • 이 λͺ¨λΈμ€ klue/roberta-largeλ₯Ό ν•œκ΅­μ–΄ Machine Reading Comprehensionλ₯Ό μœ„ν•΄ KorQuAD 데이터 2.1 version 27,423개의 데이터λ₯Ό ν•™μŠ΅μ‹œμΌœ λ§Œλ“  λͺ¨λΈμž…λ‹ˆλ‹€.

πŸ“ What Should Know

  • KorQuAD v2.1의 원본 데이터가 μ•„λ‹Œ ν•˜μ΄νΌλ§ν¬, νƒœκ·Έ, μœ λ‹ˆμ½”λ“œ BOMλ₯Ό μ œκ±°ν•˜μ—¬ μ „μ²˜λ¦¬λ₯Ό ν•˜μ˜€κ³ , context 길이가 7500이 λ„˜μ–΄κ°„ 데이터듀은 μ œμ™Έν•˜μ—¬ 27,423개의 데이터셋을 μ΄μš©ν•˜μ—¬ ν•™μŠ΅μ‹œμΌ°μŠ΅λ‹ˆλ‹€.
  • 원본 데이터 링크 : https://korquad.github.io/

πŸ“ Getting Started

from transformers import AutoConfig, AutoModelForQuestionAnswering, AutoTokenizer

config = AutoConfig.from_pretrained('uomnf97/klue-roberta-finetuned-korquad-v2')
tokenizer = AutoTokenizer.from_pretrained('uomnf97/klue-roberta-finetuned-korquad-v2')
model = AutoModelForQuestionAnswering.from_pretrained('uomnf97/klue-roberta-finetuned-korquad-v2',config=config)
Downloads last month
54
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.