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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
Threagile empowers teams to implement Agile Threat Modeling with remarkable ease, seamlessly integrating into DevSecOps workflows. This open-source toolkit allows users to represent an architecture and its assets in a flexible, declarative manner using a YAML file, which can be edited directly within an IDE or any YAML-compatible editor. When the Threagile toolkit is executed, it processes a series of risk rules that perform security evaluations on the architecture model, generating a comprehensive report detailing potential vulnerabilities and suggested mitigation strategies. Additionally, visually appealing data-flow diagrams are automatically produced, along with various output formats such as Excel and JSON for further analysis. The tool also supports ongoing risk management directly within the Threagile YAML model file, enabling teams to track their progress on risk mitigation effectively. Threagile can be operated through the command line, and for added convenience, a Docker container is available, or it can be set up as a REST server for broader accessibility. This versatility ensures that teams can choose the deployment method that best fits their development environment.
API Access
Has API
API Access
Has API
Integrations
Docker
Aim
Alpaca
Comet
Discord
Hugging Face
JSON
Kubernetes
Llama 2
MLflow
Integrations
Docker
Aim
Alpaca
Comet
Discord
Hugging Face
JSON
Kubernetes
Llama 2
MLflow
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Uber AI
Founded
2016
Country
United States
Website
ludwig.ai/latest/
Vendor Details
Company Name
Threagile
Website
threagile.io
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization