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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
Tasks like generating offers, setting prices, and calculating expenses can consume a lot of time; however, with SaleConfig, these processes can now be efficiently automated. The Configurator, which is the core component of SaleConfig, is responsible for maintaining product details along with sales-related information, such as costs and pricing. This automation substantially lightens the workload for product designers and administrators managing cost and sales data. The configurator's sophisticated algorithm enables the establishment of various dependencies among product parameters. With an intuitive interface, users can effortlessly and promptly prepare their products for sale. SaleConfig not only assists in preparing offers but also provides insights into all available options, configurations, and dependencies. As a result, even less experienced sales personnel can generate offers with ease, while simultaneously reducing the time required for their training. Moreover, your sales team can operate remotely and access SaleConfig, requiring only an internet connection to do so effectively. This level of accessibility ensures that sales processes remain seamless, regardless of location.
API Access
Has API
API Access
Has API
Integrations
Aim
Alpaca
Comet
Discord
Docker
Hugging Face
Kubernetes
Llama 2
MLflow
Python
Integrations
Aim
Alpaca
Comet
Discord
Docker
Hugging Face
Kubernetes
Llama 2
MLflow
Python
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
Uber AI
Founded
2016
Country
United States
Website
ludwig.ai/latest/
Vendor Details
Company Name
SaleConfig
Founded
2007
Country
Poland
Website
www.saleconfig.com
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
CPQ
2D Drawing
3D Modeling
Approval Workflow
Guided Selling
Product Configurator
Proposal Generation
Quotes / Estimates
Renewal Management
Self Service Portal
eCommerce