# orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch

Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch

Repository: https://github.com/orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch
Canonical: https://ross.abutalabs.com/products/prototypical-networks-for-few-shot-learning-pytorch
Language: Python
License: MIT
License Family: permissive
Topics: python, pytorch, cnn, prototypical-networks
Last push: 2022-04-05T12:15:25+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3138, "days_push": 1611, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1078, forks 217 (observed 2026-08-28T04:03:29.749726+00:00)

## What it is
A PyTorch implementation of Prototypical Networks for few-shot learning, including the prototypical loss and episode-based batch sampler. It reproduces the reference paper's methodology on the Omniglot dataset with Vinyals-style splits.

## Use cases
- implement prototypical networks in pytorch
- few-shot image classification
- reproduce results from the prototypical networks paper
- learn meta-learning and episode-based training
- train on the omniglot dataset with vinyals splits

## When to choose
- you want a simple, readable PyTorch implementation of Prototypical Networks
- you need a prototypical loss or episodic batch sampler to reuse in your own few-shot project
- you want to reproduce paper results on Omniglot

## When to avoid
- you need production-ready, actively maintained few-shot learning frameworks
- you want support for many datasets or modern meta-learning methods out of the box
- you need non-PyTorch (e.g., TensorFlow) implementations

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: machine-learning, deep-learning, computer-vision
- platform: python
- tags: few-shot-learning, pytorch, prototypical-networks, meta-learning, omniglot, cnn

## Member repositories
- orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:29.749726+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:53:11.507274+00:00, confidence not recorded.
  - readme: https://github.com/orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch (fetched 2026-08-28T04:03:29.749726+00:00, sha 7a3da08ec911)
- Data as of 2026-08-30T08:39:29.467469+00:00.