KISTI-KONI/KONI-Llama3.1-70B-Instruct-20241115

Hugging Face
TEXT GENERATIONConcurrency Cost:4Model Size:70BQuant:FP8Ctx Length:32kLicense:llama3.1Architecture:Transformer0.0K Warm

KONI-Llama3.1-70B-Instruct-20241115 is a 70 billion parameter instruction-tuned large language model developed by KISTI (Korea Institute of Science and Technology Information), built upon Meta-Llama-3.1-70B-Instruct. This model is specifically specialized and optimized for science and technology tasks, leveraging a vast corpus of scientific and technological data. It demonstrates enhanced performance across reasoning, math, writing, coding, and comprehension, making it highly effective for scientific research and technical applications. The model was fine-tuned using approximately 11k SFT data and 7k DPO data, including Korean-translated public datasets.

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KISTI-KONI/KONI-Llama3.1-70B-Instruct-20241115: Science & Technology Specialized LLM

KONI (KISTI Open Natural Intelligence) is a large language model developed by the Korea Institute of Science and Technology Information (KISTI), specifically designed for science and technology domains. This 70 billion parameter instruction-tuned model is built on the Meta-Llama-3.1-70B-Instruct base.

Key Capabilities & Features

  • Science and Technology Specialization: Explicitly trained on a vast, specialized corpus of scientific and technological data, making it highly effective for domain-specific tasks.
  • Enhanced Performance: Demonstrates significant performance improvements over previous KONI versions.
  • Fine-tuning: Utilizes Supervised Fine-Tuning (SFT) with approximately 11k data points and Direct Preference Optimization (DPO) with 7k data points, including internally generated and publicly available data, with Korean translations.

Benchmark Performance

Evaluated using the LogicKor benchmark, KONI-Llama3.1-70B-Instruct-20241115 achieved an Overall Score of 9.38, with strong results in:

  • Reasoning: 9.07
  • Math: 9.65
  • Coding: 9.65
  • Comprehension: 9.86

Ideal Use Cases

This model is particularly well-suited for applications requiring deep understanding and generation within scientific and technological contexts, including research assistance, technical documentation, and specialized Q&A in these fields.