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pytorch-meta

tristandeleu/pytorch-meta

Extensions and data-loaders for few-shot learning & meta-learning in PyTorch

GitHub Website

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2.1k stars264 forksLast push 3y Python MIT

Decision brief

PyTorch-Meta focuses on facilitating few-shot learning and meta-learning with PyTorch, offering extensions and data-loaders specifically for these tasks.

Good fit when

When developing models that require handling few-shot learning scenarios where only a small amount of labeled data is available.
For researchers or developers interested in leveraging pre-built modules and data-loaders to accelerate the prototyping phase in meta-learning projects.

Avoid when

If your project requires extensive support for traditional deep learning tasks, as PyTorch-Meta does not offer comprehensive utilities beyond few-shot learning and meta-learning.
For those strictly adhering to a single ecosystem that does not include the PyTorch framework or its specific versions below 1.4.

Observed Jul 16, 2026 · Source: enrich:decision_facts

pytorch-meta alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Dormant (1113d since push); As of 2w
Provenance: Not a fork · Personal account; As of 2w
Security (OSV): No lockfile; As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install pytorch-meta

PyPI

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Provides modules that facilitate the development of few-shot learning and meta-learning models using PyTorch framework.

Capability facts

Languages: python
Source: github.language · Aug 4, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 4, 2026)

You can install Torchmeta either using Python's package manager pip, or from source. To avoid any conflict with your existing

Source link

README

Installation

You can install Torchmeta either using Python's package manager pip, or from source. To avoid any conflict with your existing Python setup, it is suggested to work in a virtual environment with virtualenv. To install virtualenv:

pip install --upgrade virtualenv
virtualenv venv
source venv/bin/activate

Requirements

Python 3.6 or above
PyTorch 1.4 or above
Torchvision 0.5 or above

Using pip

This is the recommended way to install Torchmeta:

pip install torchmeta

From source

You can also install Torchmeta from source. This is recommended if you want to contribute to Torchmeta.

git clone https://github.com/tristandeleu/pytorch-meta.git
cd pytorch-meta
python setup.py install

For agents

This page has a .md twin and JSON over the API.

/tools/tristandeleu-pytorch-meta.md GET /api/graphcanon/tools/tristandeleu-pytorch-meta GET /api/graphcanon/graph?tool=tristandeleu-pytorch-meta