Predibase
Predibase is a developer platform that enables efficient fine-tuning and serving of open-source large language models (LLMs) with state-of-the-art infrastructure in the cloud or private deployments.
https://www.predibase.com/?ref=aipure
Product Information
Updated:Mar 20, 2025
Predibase Monthly Traffic Trends
Predibase received 78.6k visits last month, demonstrating a Significant Growth of 180.7%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history trafficWhat is Predibase
Predibase is a low-code/no-code end-to-end platform built for developers to customize and deploy open-source language models. Founded by the team behind popular open-source projects Ludwig and Horovod from Apple and Uber, Predibase makes it easy for engineering teams to cost-efficiently fine-tune and serve small open-source LLMs on state-of-the-art infrastructure, without sacrificing quality. The platform is currently being used by both Fortune 500 companies and high-growth startups like Nubank, Forethought, and Checkr.
Key Features of Predibase
Predibase is a developer platform that enables efficient fine-tuning and serving of open-source Large Language Models (LLMs). It offers state-of-the-art fine-tuning techniques including quantization, low-rank adaptation, and memory-efficient distributed training. The platform features reinforcement fine-tuning capabilities, multi-LoRA serving through LoRAX, and can be deployed either in Predibase's cloud or private infrastructure. It provides enterprise-grade reliability with features like multi-region high availability, logging, and SOC 2 Type II certification.
Turbo LoRA Multi-Model Serving: Serves hundreds of fine-tuned models on a single GPU with 4x faster throughput than traditional solutions, using LoRAX-powered technology
Reinforcement Fine-Tuning (RFT): Enables model training with minimal data requirements using reward functions for continuous learning and improvement
Flexible Deployment Options: Offers both cloud-hosted and private infrastructure deployment with autoscaling capabilities and dedicated GPU resources
Enterprise-Grade Security: Provides SOC 2 Type II certification, multi-region high availability, and comprehensive logging and metrics
Use Cases of Predibase
Background Check Automation: Checkr uses Predibase to streamline background checks with fine-tuned models, achieving 5x cost reduction compared to GPT-4
Customer Service Enhancement: Convirza leverages Predibase to efficiently serve 60 adapters for handling variable customer service workloads with fast response times
Enterprise Process Automation: Marsh McLennan utilizes Predibase for cost-effective automation of various enterprise processes, saving over 1 million hours of team time
Conservation Data Analysis: WWF employs customized LLMs through Predibase to generate insights from their large corpus of conservation project reports
Pros
Cost-effective with 5x reduction in costs compared to GPT-4
High performance with 4x faster throughput using Turbo LoRA
Flexible deployment options in cloud or private infrastructure
Enterprise-grade security and reliability features
Cons
Requires technical expertise to fully utilize all features
Limited to open-source LLMs only
Private serverless deployments have 12-hour inactivity timeout
How to Use Predibase
Sign up for Predibase: Go to predibase.com and sign up for a free trial account or contact sales for enterprise options. You'll need to generate an API token from Settings > My Profile once logged in.
Install Predibase SDK: Install the Predibase Python SDK using: pip install predibase
Connect to Predibase: Initialize the Predibase client using your API token: from predibase import Predibase; pb = Predibase(api_token='YOUR_TOKEN')
Prepare your training data: Upload or connect your training dataset through the UI (Data > Connect Data) or programmatically. Predibase supports various data sources including file upload, Snowflake, Databricks, and Amazon S3. Aim for 500-1000+ diverse examples.
Configure fine-tuning: Create a fine-tuning configuration specifying the base model (e.g. Mistral, Llama), dataset, and prompt template. Advanced users can adjust parameters like learning rate and temperature.
Launch fine-tuning: Start the fine-tuning job through the UI or SDK. Monitor training progress and evaluation metrics. The best performing checkpoint will be automatically selected.
Deploy model: Deploy your fine-tuned model using: pb.deployments.create(name='my-model', config=DeploymentConfig(base_model='model-name'))
Query the model: Generate predictions using: client = pb.deployments.client('my-model'); response = client.generate('Your prompt here')
Monitor and scale: Monitor model performance, costs and scaling through the UI dashboard. Predibase automatically handles GPU scaling and load balancing.
Predibase FAQs
Predibase is a developer platform for fine-tuning and serving open-source Large Language Models (LLMs). It allows users to customize and serve open-source models that can outperform GPT-4, all within their cloud or Predibase's infrastructure.
Predibase Video
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Analytics of Predibase Website
Predibase Traffic & Rankings
78.6K
Monthly Visits
#484800
Global Rank
#5955
Category Rank
Traffic Trends: Dec 2024-Feb 2025
Predibase User Insights
00:01:14
Avg. Visit Duration
2.23
Pages Per Visit
48.39%
User Bounce Rate
Top Regions of Predibase
US: 31.69%
IN: 12.08%
DE: 11%
GB: 6.31%
PL: 5.63%
Others: 33.29%
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