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| title: TRIBE V2 — Brain Response Prediction | |
| emoji: 🧠 | |
| colorFrom: indigo | |
| colorTo: yellow | |
| sdk: gradio | |
| sdk_version: "6.11.0" | |
| python_version: "3.12" | |
| app_file: app.py | |
| pinned: false | |
| license: cc-by-nc-4.0 | |
| hardware: cpu-basic | |
| # TRIBE V2 — Brain Response Prediction | |
| Predicts fMRI brain responses to **video, audio, and text** using Meta's TRIBE V2 foundation model. | |
| ## Features | |
| - **Text Scorer** — Paste a script/hook, get brain engagement scores (~30s) | |
| - **Video Scorer** — Upload a video for full multimodal analysis (~2-5 min) | |
| - **A/B Tester** — Compare two text versions head-to-head | |
| - **API** — Programmatic JSON access | |
| ## How It Works | |
| TRIBE V2 combines LLaMA 3.2-3B (text), V-JEPA2 (video), and Wav2Vec-BERT (audio) to predict cortical surface activations across 20,484 brain vertices. Scores are derived from region-of-interest analysis using the Destrieux atlas. | |
| ## Scores | |
| - **Attention Capture** — Will they stop scrolling? | |
| - **Emotional Valence** — Does it trigger feelings? | |
| - **Language Processing** — Is the message clear? | |
| - **Visual Imagery** — Are visuals compelling? | |
| - **Viral Potential** — Composite engagement score | |
| ## Citation | |
| ``` | |
| @article{tribe2024, | |
| title={A Foundation Model of Vision, Audition, and Language for In-Silico Neuroscience}, | |
| author={Meta FAIR}, | |
| year={2024} | |
| } | |
| ``` | |