Question: Is there a tool that allows me to customize and extend my large language models for better performance and flexibility?

Predibase is a full-fledged platform that lets developers fine-tune and serve LLMs in a high-performance, cost-effective way. It supports a variety of models, including Llama-2, Mistral and Zephyr, with options like quantization and low-rank adaptation. Predibase also offers a low-cost serving foundation, free serverless inference, and dedicated deployments with high-priority access to A100 GPUs.

Lamini is another powerful option geared for enterprise software teams. It lets you build, manage and deploy LLMs on your own data. Lamini comes with options like memory tuning for high accuracy, deployment to multiple environments and guaranteed JSON output. It can be installed on-premise or in the cloud, scaling up to thousands of LLMs and offering a full platform for managing the model lifecycle.

For those who want data sovereignty and self-sufficiency, Prem offers a simple environment for creating personalized LLMs. With abilities like prompt engineering, model testing and on-premise deployment, Prem lets companies train models with their own prompts and fine-tune for their own business needs. It also comes with a library of open-source SLMs for more flexibility.

Last, Turing is a good platform for improving LLM performance and for building custom genAI applications. It comes with model testing tools, sophisticated reasoning abilities and integration with agents and tooling. Turing also offers engineering services for LLM training and optimization, so it's a good choice for companies that need more customized AI.