TimeSformer model pre-trained on Kinetics-600. It was introduced in the paper TimeSformer: Is Space-Time Attention All You Need for Video Understanding? by Tong et al. and first released in this repository. Disclaimer: The team releasing TimeSformer did not write a model card for this model so this model card has been written by fcakyon. You can use the raw model for video classification into one of the 600 possible Kinetics-600 labels.
**A Foundation Model of Vision, Audition, and Language for In-Silico Neuroscience** 📄 Paper ▶️ Demo | 🤗 Weights TRIBE v2 is a deep multimodal brain encoding model that predicts fMRI brain responses to naturalistic stimuli (video, audio, text). It combines state-of-the-art feature extractors — **LLaMA 3.2** (text), **V-JEPA2** (video), and **Wav2Vec-BERT** (audio) — into a unified Transformer architecture that maps multimodal representations onto the cortical surface.
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