--- license: other ---
Arcee Nova
## Overview Arcee-Nova is our highest performing open source model, setting new benchmarks in AI capabilities. Evaluated on the same stack as the OpenLLM Leaderboard 2.0, Arcee-Nova achieves an impressive 9.15 on MT-Bench, making it the top-performing open source model on the leaderboard. Its performance approaches that of GPT-4 from May 2023, marking a significant milestone in open source AI development. GGUFs available [here](https://huggingface.co/arcee-ai/Arcee-Nova-GGUF) ## Capabilities and Use Cases Arcee-Nova excels across a wide range of language tasks, demonstrating particular strength in: 1. **Reasoning**: Solving complex problems and drawing logical conclusions. 2. **Creative Writing**: Generating engaging and original content across various genres. 3. **Coding**: Assisting with programming tasks, from code generation to debugging. 4. **General Language Understanding**: Comprehending and generating human-like text in diverse contexts. Here are some examples of Arcee-Nova's capabilities: 1. **Complex Problem Solving**: ```markdown [Insert a complex reasoning or problem-solving example here] ``` 2. **Creative Writing**: ```markdown [Insert a creative writing sample here] ``` 3. **Code Generation**: ```python [Insert a code generation example here] ``` ## Business Applications Arcee-Nova can be applied to various business tasks: - **Customer Service**: Implement sophisticated chatbots and virtual assistants. - **Content Creation**: Generate high-quality written content for marketing and documentation. - **Software Development**: Accelerate coding processes and improve code quality. - **Data Analysis**: Enhance data interpretation and generate insightful reports. - **Research and Development**: Assist in literature reviews and hypothesis generation. - **Legal and Compliance**: Automate contract analysis and regulatory compliance checks. - **Education and Training**: Create adaptive learning systems and intelligent tutoring programs. ## Evaluations
Arcee Nova Evaluations
[Additional evaluation charts and scores to be added here] ## Acknowledgments We extend our gratitude to the open source AI community, whose collective efforts have paved the way for breakthroughs like Arcee-Nova. Their commitment to transparency and collaboration continues to drive innovation in the field of artificial intelligence. We also would like to extend our thanks to the Qwen team - without Qwen2-72B this would not be possible. ## Future Directions As we release Arcee-Nova to the public, we look forward to seeing how researchers, developers, and businesses will leverage its capabilities to push the boundaries of what's possible with AI. We remain committed to advancing open source AI technology and invite the community to explore, contribute, and build upon Arcee-Nova. --- *Note: This README was written with assistance from Arcee-Nova.*