Edentns/DataVortexS-10.7B-dpo-v1.8
Edentns/DataVortexS-10.7B-dpo-v1.8 is a 10.7 billion parameter language model developed by Kwangseok Yang, Jeongwon Choi, Seunghyun Choi, and Hyoseok Choi. Built upon the megastudy/M-SOLAR-10.7B-v1.3 base model, it is instruction-tuned using the Alpaca (Chat) format. This model demonstrates strong performance on Korean language benchmarks, including Ko LM Eval Harness and Ko-LLM-Leaderboard, making it suitable for Korean-centric conversational AI applications.
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DataVortexS-10.7B-dpo-v1.8 Overview
DataVortexS-10.7B-dpo-v1.8 is a 10.7 billion parameter language model developed by a team including Kwangseok Yang and Seunghyun Choi. It is built on the megastudy/M-SOLAR-10.7B-v1.3 base model and has been instruction-tuned following the Alpaca (Chat) format, making it well-suited for conversational tasks.
Key Capabilities & Performance
- Instruction Following: Utilizes the Alpaca (Chat) instruction format for clear and structured interactions.
- Korean Language Proficiency: Demonstrates strong performance across various Korean language benchmarks.
- Ko LM Eval Harness: Achieves an average of 0.789423 on 50-shot evaluations, with notable scores in
kobest_sentineg(0.949596) andkobest_boolq(0.923032). - Ko-LLM-Leaderboard: Scores an average of 58.15, with specific results like 66.68 on Ko-HellaSwag and 61.04 on Ko-CommonGen V2.
- Ko LM Eval Harness: Achieves an average of 0.789423 on 50-shot evaluations, with notable scores in
- Implementation: Provides a
chat_templateinstruction format for easy integration withtransformerslibrary, including example Python code for generation.
Good For
- Developing conversational AI applications in Korean.
- Tasks requiring strong understanding and generation of Korean text.
- Researchers and developers looking for a performant Korean LLM in the 10B parameter range.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.