NCSOFT/Llama-VARCO-8B-Instruct

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:Sep 12, 2024License:llama3.1Architecture:Transformer0.1K Warm

NCSOFT/Llama-VARCO-8B-Instruct is an 8 billion parameter generative language model developed by NC Research, Language Model Team. Built upon Meta-Llama-3.1-8B, it is continually pre-trained with Korean and English datasets and fine-tuned using SFT and DPO in Korean. This model is specifically optimized for high proficiency in Korean language understanding and generation, while maintaining strong English capabilities. It is best suited for applications requiring robust bilingual performance, particularly in Korean contexts.

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Overview

Llama-VARCO-8B-Instruct is an 8 billion parameter generative language model developed by NC Research, Language Model Team. It is based on the meta-llama/Meta-Llama-3.1-8B architecture and has undergone extensive continual pre-training using both Korean and English datasets. This process aims to significantly enhance its understanding and generation capabilities in Korean, while simultaneously preserving its proficiency in English.

Key Differentiators

  • Bilingual Optimization: Specifically designed to excel in Korean through additional training, while maintaining strong English performance.
  • Fine-tuning for Korean Preferences: Utilizes Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) with Korean data to align its responses with human preferences.
  • Strong Korean Performance: Achieves an overall LogicKor score of 8.82, outperforming Meta-Llama-3.1-8B-Instruct (5.42), Gemma-2-9B-Instruct (7.98), and Qwen2-7B-Instruct (6.71) on Korean-centric evaluations.

Recommended Use Cases

  • Applications requiring high-quality Korean language generation and understanding.
  • Bilingual (Korean-English) conversational AI and content creation.
  • Tasks benefiting from a model fine-tuned to Korean human preferences.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

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