Saxo/Linkbricks-Horizon-AI-Korean-Mistral-Nemo-sft-dpo-12B

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:12BQuant:FP8Ctx Length:32kPublished:Aug 7, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

The Saxo/Linkbricks-Horizon-AI-Korean-Mistral-Nemo-sft-dpo-12B is a 12 billion parameter Korean language model developed by Linkbricks Horizon-AI, fine-tuned from the Mistral-Nemo-Instruct-2407 base model. It was trained using SFT and DPO methods on Korean, Chinese, English, and Japanese cross-training data, including logical data, to enhance its ability to handle complex Korean logic problems. This model is particularly strengthened for high-level analysis of customer reviews, social postings, and coding tasks, featuring a context window size of 128K tokens.

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Saxo/Linkbricks-Horizon-AI-Korean-Mistral-Nemo-sft-dpo-12B Overview

Developed by Linkbricks Horizon-AI's data scientist Yunsung Ji (Saxo), this 12 billion parameter model is a Korean language model fine-tuned from the Mistral-Nemo-Instruct-2407 base. The fine-tuning process involved Supervised Fine-Tuning (SFT) followed by Direct Preference Optimization (DPO) using four H100-80G GPUs on KT-CLOUD.

Key Capabilities

  • Multilingual Cross-Augmentation: Trained with Korean, Chinese, English, and Japanese cross-training data, alongside logical data, to improve multilingual understanding and logical reasoning.
  • Complex Korean Logic: Specifically designed to address and solve intricate logical problems in Korean.
  • Enhanced Analysis: Strengthened for high-level analysis of customer reviews and social media postings.
  • Coding Proficiency: Demonstrates enhanced capabilities in coding tasks.
  • Extended Context Window: Features a substantial context window size of 128K tokens, allowing for processing longer inputs.
  • Tokenizer Consistency: Utilizes the base model's tokenizer without word expansion.

Performance & Training Details

Good For

  • Applications requiring advanced Korean language understanding and logical problem-solving.
  • Analyzing customer feedback and social media content in Korean.
  • Coding assistance and generation in a multilingual context.
  • Use cases benefiting from a large context window for processing extensive text.