---
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
---

> **Mirror** of [`mlboydaisuke/VJEPA2-ViTL-SSv2-CoreAI`](https://huggingface.co/mlboydaisuke/VJEPA2-ViTL-SSv2-CoreAI) — the canonical repo ([CoreAI Model Zoo](https://github.com/john-rocky/coreai-model-zoo)). Updates land there first.


# 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) |
| `ios/vjepa2_ssv2_fp16.h18p.aimodelc` | iOS AOT bundle (iPhone, A18 Pro+ GPU) |
| `macos/labels.json`, `ios/labels.json` | 174 SSv2 class names |
| `macos/metadata.json` | I/O + preprocessing spec |

**Live demo app**: [coreai-video](https://github.com/john-rocky/coreai-model-zoo/tree/main/apps/coreai-video)
— camera → live top-3 actions. iPhone 17 Pro: ~0.34 s per 16-frame clip.

## 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).