facebookresearch/tribev2

Health v2 · maintenance only

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3172 stars · 694 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

TRIBE v2 is a multimodal deep learning model from Meta AI that predicts fMRI brain responses to naturalistic video, audio, and text stimuli. It provides pretrained weights, an inference API, and training pipelines for in-silico neuroscience research.

Use cases

• predict fMRI brain responses to videos
• model how the brain processes audio and language
• run brain encoding experiments with pretrained models
• visualize predicted activity on a cortical surface
• train a multimodal brain encoding model from scratch

When to choose

• you need to predict brain activity from multimodal stimuli like video, audio, or text
• you are doing computational neuroscience or neural encoding research
• you want a pretrained brain encoding model with HuggingFace weights and a Colab demo

When to avoid

• you need a clinically validated tool for medical diagnosis
• you require a permissively licensed model for commercial use (CC BY-NC 4.0)
• you lack GPU resources or fMRI domain context for training

Facets

library · maturity active

machine-learning deep-learning nlp audio-processing video-processing deep-learning machine-learning artificial-intelligence python brain-encoding fmri multimodal transformer computational-neuroscience research-code pytorch neuroscience gpu linux

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markdown · JSON · MCP: product_card(name="facebookresearch/tribev2")