lucidrains/perceiver-pytorch

Health v2 · maintenance only

Adoption not part of the score

1217 stars · 140 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of the Perceiver architecture (General Perception with Iterative Attention) and its follow-up Perceiver IO. It provides ready-to-use model classes for processing multimodal inputs like images and video via cross-attention to a latent array.

Use cases

• implement perceiver architecture in pytorch
• train a model on images with iterative attention
• use perceiver io for flexible output sequences
• experiment with cross-attention on multimodal data
• reproduce deepmind perceiver paper results

When to choose

• you want a pip-installable PyTorch implementation of Perceiver or Perceiver IO
• you need a research baseline for latent-attention architectures
• you want to experiment with attention over arbitrary input modalities

When to avoid

• you need a production-trained model with pretrained weights
• you require a full training pipeline or dataset tooling
• you need architectures beyond Perceiver, like standard transformers

Facets

library · maturity active

machine-learning deep-learning deep-learning machine-learning artificial-intelligence python perceiver attention-mechanism transformers pytorch research-implementation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="lucidrains/perceiver-pytorch")