Ludwig

Ludwig

Uber AI
+
+

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About

Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Build custom models with ease: a declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Optimized for scale and efficiency: automatic batch size selection, distributed training (DDP, DeepSpeed), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Expert level control: retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Modular and extensible: experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. Think building blocks for deep learning.

About

MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers interested in a low-code framework to build custom AI models like LLMs and other deep neural networks

Audience

Companies looking for an open source platform solution for the machine learning lifecycle

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Uber AI
Founded: 2016
United States
ludwig.ai/latest/

Company Information

MLflow
Founded: 2018
United States
mlflow.org

Alternatives

DeepSpeed

DeepSpeed

Microsoft

Alternatives

Union Cloud

Union Cloud

Union.ai
MLBox

MLBox

Axel ARONIO DE ROMBLAY
DVC

DVC

iterative.ai

Categories

Categories

Integrations

Docker
Kubernetes
Aim
Azure Machine Learning
Azure Marketplace
Comet LLM
Databricks
Determined AI
Flyte
Jozu
Kedro
Microsoft 365
RAY
Ragas
RapidSOS
TensorBoard
TensorFlow
UbiOps
Weights & Biases
conDati

Integrations

Docker
Kubernetes
Aim
Azure Machine Learning
Azure Marketplace
Comet LLM
Databricks
Determined AI
Flyte
Jozu
Kedro
Microsoft 365
RAY
Ragas
RapidSOS
TensorBoard
TensorFlow
UbiOps
Weights & Biases
conDati
Claim Ludwig and update features and information
Claim Ludwig and update features and information
Claim MLflow and update features and information
Claim MLflow and update features and information