EAGLE is a decoder causal language model with 3.1 billion parameters developed by the Electronics and Telecommunications Research Institute (ETRI) in South Korea, focusing on the STEM fields, especially mathematics and quantitative reasoning. This model has been pre-trained on 720 billion tokens and uses a LLaMA-compatible architecture. However, it is not a general-purpose language model and requires additional fine-tuning to be used in applications such as chatbots.

Natural Language ProcessingTransformersKorean

LLama-3-8B-Tele is a language model with 8 billion parameters optimized specifically for the telecommunications field. It is based on Meta's LLama-3-8B architecture and is continuously pre - trained on a telecommunications dataset of 2.5 billion tokens. It performs excellently on telecommunications - related tasks while maintaining the original model's capabilities in common sense, language understanding, and logical reasoning.

Natural Language ProcessingSafetensorsEnglish

Phi-1.5-Tele is a language model specifically designed for the telecommunications field. Based on Microsoft's phi-1.5 model, it has been continuously pre-trained on a large-scale telecommunications dataset and performs excellently in telecommunications benchmark tests. At the same time, it maintains comparable performance to the original model in benchmark tests such as common sense, language understanding, and logical reasoning.

Natural Language ProcessingSafetensorsMultiple Languages