References
- Hugo et al. 2023. Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023).
- Optimization could cut the carbon footprint of AI training by up to 75%: https://news.umich.edu/optimization-could-cut-the-carbon-footprint-of-ai-training-by-up-to-75/
- Retrieval Augmented Generation (RAG) in Azure AI Search: https://learn.microsoft.com/en-us/azure/search/retrieval-augmented-generation-overview
- RAG, AI, and Salesforce: Explained: https://gptfy.ai/blog/rag-ai-and-salesforce-explained/#:~:text=RAG%20is%20an%20AI%20technology,positions%20companies%20for%20future%20success
- Ollama: https://ollama.com/
- PolyAI. (2020). Task-specific datasets. GitHub repository. Retrieved from https://github.com/PolyAI-LDN/task-specific-datasets
- Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., Rodriguez, A., Joulin, A., Grave, E., & Lample...
