Sagify

Sagify offers a streamlined solution for training and deploying Machine Learning and Deep Learning models on AWS Sagemaker. This command-line tool simplifies and enhances the process, making it more user-friendly and efficient.

About Sagify

Sagify is a command-line tool for training and deploying machine learning and large language models on AWS SageMaker. It handles provisioning, distributed training, hyperparameter tuning and deployment, and includes an LLM Gateway with a FastAPI-based REST API that offers one interface to proprietary and open-source models. Batch inference and embeddings are supported. It requires Python, Docker and a configured AWS CLI. Pricing is not stated in the available sources.

Best for: machine learning engineers, data scientists, teams deploying LLMs on AWS

Key features

Command-line interface for managing ML workflows on AWS SageMaker
LLM Gateway gives one interface to open-source and proprietary models
Automates provisioning, training, tuning and deployment
FastAPI-based REST API serves as the gateway for LLM interactions
Supports batch inference and embeddings

Use cases

Deploying custom ML models to AWS SageMaker from the command line
Managing OpenAI, Anthropic or open-source LLMs through one gateway
Running batch inference jobs on deployed models
Running hyperparameter optimization for ML models

Pros

Handles cloud resource setup that would otherwise be manual
One API for working with multiple LLM providers

Limitations

Requires Python, Docker, and AWS CLI to be installed and configured

Screenshots

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