AI is happening. The future is updating.KONI-Llama3.1-8B-Instruct-20241024
- KONI (KISTI Open Natural Intelligence) is a specialized large language model (LLM) developed by the Korea Institute of Science and Technology Information (KISTI). This model is specifically designed for science and technology, making it highly effective for tasks in these fields. - **Specialized in Science and Technology:** The model is explicitly trained on a vast and specialized corpus of scientific and technological data. - **Enhanced Performance:** This version of KONI shows significantly improved performance compared to its initial release in December, 2023. - **Base Model:** The base model for KONI-Llama3.1-8B-Instruct-20241024 is KONI-Llama3.1-8B-Merged-20240830, which is a merger of Meta-Llama-3-8B and KISTI-KONI/KONI-Llama3.1-8B-20240824 - **Alignment:** SFT (Supervised Fine-Tuning) and DPO (Direct Preference Optimization) are applied - Approximately 11k SFT data and 7k DPO data are used. - **SFT Data:** The SFT data includes both internally generated data and publicly available data on Hugging Face, translated into Korean where necessary. - **DPO Data:** The DPO data consists of translated and curated data from argilla/dpo-mix-7k.
- KONI (KISTI Open Natural Intelligence) is a specialized large language model (LLM) developed by the Korea Institute of Science and Technology Information (KISTI). This model is specifically designed for science and technology, making it highly effective for tasks in these fields. - **Specialized in Science and Technology:** The model is explicitly trained on a vast and specialized corpus of scientific and technological data. - **Enhanced Performance:** This version of KONI shows significantly improved performance compared to its initial release in December, 2023. - **Base Model:** The base model for KONI-Llama3.1-8B-Instruct-20241024 is KONI-Llama3.1-8B-Merged-20240830, which is a merger of Meta-Llama-3-8B and KISTI-KONI/KONI-Llama3.1-8B-20240824 - **Alignment:** SFT (Supervised Fine-Tuning) and DPO (Direct Preference Optimization) are applied - Approximately 11k SFT data and 7k DPO data are used. - **SFT Data:** The SFT data includes both internally generated data and publicly available data on Hugging Face, translated into Korean where necessary. - **DPO Data:** The DPO data consists of translated and curated data from argilla/dpo-mix-7k.