Built by AI leaders from Uber, Google, Apple and Amazon. Developed and deployed with the world’s leading organizations.
Survey Report: Beyond the Buzz - Large Language Models in Production
Insights from 150 execs, data scientists, developers and product managers on the top challenges putting LLMs into production, best practices for customizing LLMs, and recommendations for success.
The Fastest Way to Build & Deploy Custom Models
Finetune and serve any ML and large language model in just a few lines of code or clicks—all within your environment, using your data, on top of a proven scalable infrastructure. Built by the team that did it all at Uber.
Build Models in Minutes
We automate the boring stuff like writing complex code so you can deliver value faster. With our declarative approach, you can accelerate AI projects with simplified training on any multi-modal dataset for any use case. Instantly connect data and start building a custom ML model or querying a pretained LLM such as Vicuna, OpenLlama, or Dolly without writing 100s of lines of low-level code.
Finetune without the Fuss
Manage, compare, and customize your models with granular-level control. Smart recommendations provided by our Data Science Copilot help you improve models while a robust set of tuning options enable experts to change anything from model weights to text encoders. Best of all, the models are your own—no more relying on external APIs.
Deploy like a Pro
Productionize AI applications without being an infra expert. Fully managed and built on Horovod and Ray, Predibase provides a flexible and scalable model serving infrastructure for batch and real-time inference. Our adaptive engines right-size compute for the demands of your job and you choose how you’d like to deploy—within the walls of your VPC, on the Predibase cloud, or export models for external use.
Production AI in Record Time
Ship models faster with the first end-to-end AI platform that’s simple enough for beginners and powerful enough for experts.
Your Models, Your Property
Start owning and stop renting ML models. The models you build and customize on Predibase are your property, deployed securely inside your VPC, with full data privacy.
Designed for Developers
Built by developers, for developers. Predibase enables any software engineer to do the work of an ML engineer in an easy-to-understand declarative way.
Managed Serverless Infrastructure
Stop wasting time managing distributed clusters–get fully managed, optimized compute configured for your needs without all the time and cost.
Built on Proven Open Source Technology
Ludwig is a deep learning toolbox to declaratively develop, train, fine-tune, test and deploy state-of-the-art models. Ludwig puts deep learning in the hands of analysts, engineers and data scientists without requiring low-level ML code.
Horovod is a distributed deep learning framework that scales PyTorch and TensorFlow training to hundreds of machines. It supports Tensorflow, Keras, Pytorch, Apache MXNet and has been used to productionize deep learning models across industries
Predibase works across any supervised machine learning use case, so if you have labeled or historical data, our platform can learn from those patterns and apply it to use cases such as: