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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Ludwig serves as a low-code platform specifically designed for the development of tailored AI models, including large language models (LLMs) and various deep neural networks. With Ludwig, creating custom models becomes a straightforward task; you only need a simple declarative YAML configuration file to train an advanced LLM using your own data. It offers comprehensive support for learning across multiple tasks and modalities. The framework includes thorough configuration validation to identify invalid parameter combinations and avert potential runtime errors. Engineered for scalability and performance, it features automatic batch size determination, distributed training capabilities (including DDP and DeepSpeed), parameter-efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and the ability to handle larger-than-memory datasets. Users enjoy expert-level control, allowing them to manage every aspect of their models, including activation functions. Additionally, Ludwig facilitates hyperparameter optimization, offers insights into explainability, and provides detailed metric visualizations. Its modular and extensible architecture enables users to experiment with various model designs, tasks, features, and modalities with minimal adjustments in the configuration, making it feel like a set of building blocks for deep learning innovations. Ultimately, Ludwig empowers developers to push the boundaries of AI model creation while maintaining ease of use.

Description

Declarative machine learning systems offer an ideal combination of flexibility and ease of use, facilitating the rapid implementation of cutting-edge models. Users concentrate on defining the “what” while the system autonomously determines the “how.” Though you can start with intelligent defaults, you have the freedom to adjust parameters extensively, even diving into code if necessary. Our team has been at the forefront of developing declarative machine learning systems in the industry, exemplified by Ludwig at Uber and Overton at Apple. Enjoy a selection of prebuilt data connectors designed for seamless compatibility with your databases, data warehouses, lakehouses, and object storage solutions. This approach allows you to train advanced deep learning models without the hassle of infrastructure management. Automated Machine Learning achieves a perfect equilibrium between flexibility and control, all while maintaining a declarative structure. By adopting this declarative method, you can finally train and deploy models at the speed you desire, enhancing productivity and innovation in your projects. The ease of use encourages experimentation, making it easier to refine models based on your specific needs.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Python Yes 
Aim Yes 
Alpaca Yes 
Amazon Redshift No 
Apache Hive No 
Comet Yes 
Discord Yes 
Docker Yes 
Hugging Face Yes 
Kubernetes Yes 
LiteLLM No 
Llama 2 Yes 
MySQL No 
Opik No 
PostgreSQL No 
RAY Yes 
Snowflake No 
TensorBoard Yes 
Triton Yes 
Weights & Biases Yes 

Integrations

Python Yes 
Aim No 
Alpaca No 
Amazon Redshift Yes 
Apache Hive Yes 
Comet No 
Discord No 
Docker No 
Hugging Face No 
Kubernetes No 
LiteLLM Yes 
Llama 2 No 
MySQL Yes 
Opik Yes 
PostgreSQL Yes 
RAY No 
Snowflake Yes 
TensorBoard No 
Triton No 
Weights & Biases No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Pay-as-you-go pricing
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Uber AI

Founded

2016

Country

United States

Website

ludwig.ai/latest/

Vendor Details

Company Name

Predibase

Country

United States

Website

predibase.com

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives

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