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README.md

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+---
+license: mit
+base_model: facebook/vjepa2-vitl-fpc16-256-ssv2
+tags:
+  - coreai
+  - apple
+  - video-classification
+  - v-jepa
+  - world-model
+  - on-device
+pipeline_tag: video-classification
+---
+
+# V-JEPA 2 (ViT-L, SSv2 action recognition) — Apple Core AI
+
+[V-JEPA 2](https://huggingface.co/facebook/vjepa2-vitl-fpc16-256-ssv2) (Meta AI) running natively on
+the Apple Core AI engine — the zoo's first **world model**: a self-supervised video encoder that
+learns by predicting in representation space (JEPA), here with the Something-Something v2 action
+head (174 classes of *physical interactions* — put/lift/push/roll/cover/pretend…).
+
+- **One bundle**: ViT-L backbone (3D RoPE attention) + attentive pooler + classifier, ~375M params,
+  fp16 ~675 MB.
+- **I/O**: `pixel_values_videos [1,16,3,256,256]` (16 frames, RGB 0..1, ImageNet mean/std) →
+  `logits [1,174]` (`labels.json`).
+- **Verified**: engine vs PyTorch reference cosine 0.999996, top-5 identical; a synthetic
+  motion probe (square moving up vs down) flips the predicted direction correctly.
+- **Speed**: ~150–180 ms per 16-frame clip on an M4 Max (GPU) — real-time video understanding.
+
+## Files
+
+| path | what |
+|---|---|
+| `macos/vjepa2_ssv2_fp16.aimodel` | fp16 bundle (macOS / JIT) |
+| `macos/labels.json` | 174 SSv2 class names |
+| `macos/metadata.json` | I/O + preprocessing spec |
+
+## Preprocessing
+
+Sample 16 frames uniformly from the clip, resize+center-crop to 256×256, scale to 0..1, normalize
+with ImageNet mean `[0.485,0.456,0.406]` / std `[0.229,0.224,0.225]`, layout `[1,16,3,256,256]`.
+
+## Credits
+
+- **Meta AI** — [V-JEPA 2](https://github.com/facebookresearch/vjepa2) (MIT).
+- Conversion + Core AI port: [coreai-model-zoo](https://github.com/john-rocky/coreai-model-zoo).