Predibase

Predibase supports a wide range of open-source LLMs including Llama (all versions), Mistral, Falcon, Code-Llama, and various others. They often update their list of supported models to include the latest in the open-source community.

Predibase uses state-of-the-art technology and efficient processes to significantly reduce the time and costs associated with fine-tuning LLMs. By supporting pre-trained and fine-tuned models via LoRA Exchange (LoRAx), they ensure lower operational costs for users.

The key features of Predibase include fast fine-tuning, cost-effective solutions, support for hundreds of LLMs, scalability with serverless and dedicated deployments, enhanced model accuracy, a user-friendly interface, efficient resource utilization, and flexible pricing plans.

Yes, Predibase offers scalable options for deployments including serverless inference endpoints and dedicated deployments. This allows users to scale their operations based on their specific needs and workload requirements.

Yes, Predibase offers a free tier which is limited to 10 tokens per day and 10 million tokens per month. This allows users to try out the platform's capabilities before committing to a paid plan.

Enterprise users can access custom pricing plans and enjoy enhanced performance with dedicated deployments. They also get priority support and flexibility to scale operations according to business needs, making it ideal for large-scale AI applications.

Predibase claims to achieve up to 40% more accuracy with their fine-tuned models compared to smaller or base models. This ensures better performance and reliable results for various AI applications.

Currently, Predibase does not support proprietary models. It focuses on fine-tuning and serving a broad range of open-source language models to meet various user needs.

Users can contact Predibase support via email at support@predibase.com. Additional company contact information such as a physical address and phone number is not provided on their website.

You can use a wide range of datasets with Predibase. Users are able to upload their datasets through the Predibase interface and configure fine-tuning parameters to match their specific needs for superior results.

Predibase is mainly used by machine learning engineers, data scientists, AI researchers, enterprises, and developers. Use cases include fine-tuning specific tasks, managing multiple LLM experiments, conducting research, deploying models at scale, and integrating models into applications.