Predibase

Predibase — The Developers Platform for Fine-tuning and Serving LLMs

Predibase is an end-to-end platform designed to help teams fine-tune, deploy, and scale large language models (LLMs) with high accuracy and speed. It combines fast, scalable training and inference infrastructure with specialized features like reinforcement fine-tuning (RFT) and Turbo LoRA to enable rapid iteration and deployment of customized models. The platform supports open-source SLMs, hosted model libraries, multi-region deployments, and enterprise-grade reliability for mission-critical workloads.

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How Predibase Works

1. Fine-tune base models or your own custom models using a library of base policies and data-efficient methods, including reinforcement fine-tuning (RFT) for continual improvement.
2. Serve fine-tuned models at scale on autoscaling infrastructure, optimized for low latency and high throughput.
3. Scale and manage deployments across multiple regions, with features like Blue/Green deployments, multi-LORA serving, and detailed observability.

Predibase emphasizes data efficiency, speed, and practical deployment capabilities, enabling teams to go from prototype to production with fewer GPUs and lower total cost of ownership.

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Key Capabilities

• Fine-tune any base model or deploy your own custom model with dedicated resources
• Reinforcement Fine-Tuning (RFT) to improve models with reward functions and limited labeled data
• High-speed inference with Turbo LoRA, enabling 4x faster throughput and efficient low-latency serving
• Multi-LoRA serving to run numerous tuned adapters on a single backbone model
• Dynamic GPU scaling for peak performance and cost control
• Cloud or on-premise (Your Cloud/Yours) deployment options to fit enterprise requirements
• Multi-region high availability, blue/green deployments, and robust monitoring/logging
• Open-source model support and access to a wide model library

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Use Cases

• Tailoring LLMs for specific domains (legal, financial, healthcare, etc.) with minimal data
• Rapid experimentation and iteration through reinforcement learning-based improvements
• Enterprise-grade deployment with reliable uptime, compliance, and scalable infrastructure

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Getting Started

• Explore base models and fine-tuning options
• Configure reward functions for RFT and start live training
• Deploy fine-tuned models with Turbo LoRA for fast, scalable serving
• Monitor performance and iterate to continuously improve accuracy

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Pricing and Resources

• Flexible pricing tied to deployment size, GPU usage, and features like RFT and Turbo LoRA
• Documentation and tutorials available to guide setup, training, and deployment
• Community and support channels for collaboration and assistance

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Core Features

• End-to-end platform for fine-tuning and serving LLMs
• Reinforcement Fine-Tuning (RFT) with live reward functions
• Turbo LoRA for 4x faster inference throughput
• Multi-LoRA serving to manage multiple adapters
• Dynamic autoscaling of GPUs for cost efficiency
• Open-source model compatibility and model library access
• Enterprise-ready deployments: multi-region, blue/green, high availability
• Flexible deployment options: cloud or on-premises (Your Cloud/Yours)
• Comprehensive observability with logging and metrics