Model Overview

mayacinka/ramonda-7b-dpo-ties is a 7 billion parameter language model developed by mayacinka. It is a merged model, combining the strengths of paulml/OGNO-7B and bardsai/jaskier-7b-dpo-v4.3 using the TIES merging method. This approach aims to leverage the distinct capabilities of its constituent models to achieve enhanced performance.

Key Performance Metrics

The model demonstrates competitive results on standard benchmarks:

• Open LLM Leaderboard Average: 76.19
  • ARC: 72.7
  • HellaSwag: 89.69
  • MMLU: 64.5
  • TruthfulQA: 77.17
  • Winogrande: 84.77
  • GSM8K: 68.92
• LLM AutoEval Average: 62.12
  • AGIEval: 44.67
  • GPT4All: 77.16
  • TruthfulQA: 77.6
  • Bigbench: 49.06

Usage and Configuration

The model is designed for text generation tasks and can be easily integrated into Python environments using the transformers library. Its configuration specifies a ties merge method with bardsai/jaskier-7b-dpo-v5.6 as the base model, and specific density and weight parameters for the merged components. The model supports float16 dtype for efficient inference.