Higgsfield

Higgsfield is an innovative tool designed to simplify the complex process of training large machine learning models on multiple nodes. It takes the frustration out of multi-node training by providing a seamless and efficient solution.

Highlights

• Effortlessly trains massive models: Higgsfield is perfect for training models with billions or even trillions of parameters, making it ideal for Large Language Models (LLMs).
• Efficiently manages GPU resources: Higgsfield gives you control over your GPU resources, allowing you to allocate them exclusively or non-exclusively for your training tasks.
• Streamlines your workflow: Seamlessly integrates with GitHub and GitHub Actions, facilitating continuous integration and deployment for your machine learning projects.

Key Features

• Robust GPU workload management: Efficiently allocates GPU resources to your training tasks, optimizing their use.
• Supports massive models: Enables training of models with billions to trillions of parameters using PyTorch's DeepSpeed API.
• Comprehensive training framework: Provides a complete solution for initiating, managing, and monitoring your multi-node training process.
• Manages resource contention: Effectively handles resource contention by queueing experiments, ensuring optimal resource utilization.