PrimeIntellect-ai/prime
Official CLI and Python SDK for Prime Intellect - access GPU compute, remote sandboxes, RL environments, and distributed training infrastructure for AI development at scale.
What it solves
Prime Intellect provides a unified interface for managing the complex infrastructure required for AI model development. It simplifies the process of accessing GPU resources, setting up training environments, running evaluations, and executing AI-generated code in secure cloud sandboxes.
How it works
The project provides a Command Line Interface (CLI) and SDKs that connect users to the Prime Lab ecosystem. It allows developers to:
- Manage Compute: Query available GPU resources, create and monitor compute pods, and access them via SSH.
- Train Models: Configure and launch hosted training runs, monitor logs and metrics, and manage checkpoints.
- Handle Environments: Access a community hub of verified environments for training and evaluation.
- Execute Code: Use a lightweight SDK to run AI-generated code in isolated cloud sandboxes.
- Evaluate: Push and manage evaluation results to a central hub.
Who it’s for
AI researchers and developers who need scalable GPU compute, hosted training infrastructure, and secure environments to train and evaluate frontier models.
Highlights
- Hosted Training: Integrated tools to launch training runs and track performance metrics.
- GPU Resource Management: Ability to filter and provision specific GPU types (e.g., H100).
- Cloud Sandboxes: Dedicated SDK for running AI-generated code safely in the cloud.
- Verified Environments Hub: Access to hundreds of pre-configured environments for consistent model testing.
- Lab Workspaces: Local setup for managing evaluations and prompt optimization (GEPA).
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