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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

DeepGit provides a superior way to address the question "why is this code there?" compared to traditional Git clients by facilitating a thorough exploration of source code history. This innovative tool builds upon the git blame feature, enabling users to easily track modifications made to specific lines or segments of code. Notably, DeepGit excels in recognizing code movements, even when lines have undergone changes that render them non-identical. Furthermore, it is available for free, making it accessible for use in both personal and commercial settings. Users can seamlessly integrate DeepGit with various IDEs that support external tools, including popular platforms like Eclipse, Visual Studio, and IntelliJ IDEA, as well as robust text editors like Sublime. For those interested in mastering its functionalities, a tour is available to demonstrate how DeepGit operates effectively. Compatible with Windows, macOS, and Linux, DeepGit generates a blame report for the chosen file and conducts an analysis of the selected line and its surrounding context to trace its origin. It's important to note that the origin identified by DeepGit may not directly align with the corresponding left counterpart. Additionally, even when focusing on a single line, DeepGit often identifies a block of lines that serves as the best match for further investigation, enhancing the user's understanding of code evolution. This capability not only clarifies the rationale behind code changes but also aids developers in maintaining better code comprehension over time.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Aim
Alpaca
Comet
Discord
Docker
Eclipse IDE
Hugging Face
Kubernetes
Llama 2
MLflow
Python
RAY
Sublime Text
TensorBoard
Triton
Visual Studio
Weights & Biases

Integrations

Aim
Alpaca
Comet
Discord
Docker
Eclipse IDE
Hugging Face
Kubernetes
Llama 2
MLflow
Python
RAY
Sublime Text
TensorBoard
Triton
Visual Studio
Weights & Biases

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
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

Syntevo

Country

Germany

Website

www.syntevo.com/deepgit/

Vendor Details

Company Name

Uber AI

Founded

2016

Country

United States

Website

ludwig.ai/latest/

Product Features

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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