openpi
Repository for running AI models with GPU requirements specified for inference and fine-tuning.
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
openpi is a repository for running AI models with specific GPU requirements for inference and fine-tuning, including LoRA and full fine-tuning modes.
Good fit when
- Use openpi when you need to run AI models with precise GPU memory requirements for inference and fine-tuning, particularly with LoRA and full fine-tuning modes.
- Consider openpi if you are working with Ubuntu 22.04 and have access to GPUs like the RTX 4090 or A100 (80GB) / H100, as it has been tested with these configurations.
Avoid when
- Avoid using openpi if your project requires multi-node training, as the current training script does not support this feature.
- Do not use openpi if you are working on an operating system other than Ubuntu 22.04, as the repository has not been tested with other systems.
- Requirements:
- The repository requires an NVIDIA GPU with at least 8 GB of memory for inference, 22.5 GB for fine-tuning with LoRA, and 70 GB for full fine-tuning.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Active (24d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- No lockfile
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install openpiSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository contains code for running AI models, with a focus on specifying GPU requirements for different modes of operation, including inference and fine-tuning with LoRA and full fine-tuning.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Sep 18, 2026
Categories
Tags
README
Requirements To run the models in this repository, you will need an NVIDIA GPU with at least the following specifications. These estimations assume a single GPU, but you can also use multiple GPUs with model parallelism to reduce per GPU memory requirements by configuring in the...
For agents
This page has a .md twin and JSON over the API.