sethuiyer/OpenDolphinHermes_Llama2_7B
OpenDolphinHermes_Llama2_7B is a 7 billion parameter Llama 2-based model created by sethuiyer, formed by a mergekit SLERP of cognitivecomputations/dolphin-llama2-7b and Tensoic/Llama-2-openhermes. This model aims to achieve performance comparable to the base Llama 2 13B model, demonstrating strong capabilities across various benchmarks including ARC, HellaSwag, MMLU, and TruthfulQA. It is designed for general-purpose conversational AI and natural language processing tasks, offering a robust solution within a smaller parameter count.
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Overview
sethuiyer/OpenDolphinHermes_Llama2_7B is a 7 billion parameter language model built upon the Llama 2 architecture. It was created using a mergekit SLERP operation, combining the strengths of two distinct models: cognitivecomputations/dolphin-llama2-7b and Tensoic/Llama-2-openhermes.
Key Capabilities & Performance
The primary goal of this merge was to develop a 7B model that performs comparably to the base Llama 2 13B model. Benchmarking on the OpenLLM Leaderboard shows competitive results:
- Average Score: 54.24
- AI2 Reasoning Challenge (ARC): 55.03
- HellaSwag: 78.74
- MMLU: 52.25
- TruthfulQA: 46.10
- Winogrande: 73.16
- GSM8k: 20.17
These scores indicate its proficiency in reasoning, common sense, factual knowledge, and question answering, positioning it as a capable model for various NLP tasks.
Usage
The model utilizes a ChatML prompt template, making it suitable for conversational applications. It can be easily integrated into projects using the Hugging Face transformers library, with example Python code provided for text generation.