---
license: apache-2.0
base_model: robbyant/lingbot-video-dense-1.3b
pipeline_tag: text-to-video
library_name: coreai
tags:
- coreai
- core-ai
- coreai-fabric
- aimodel
- coreml
- apple
- apple-silicon
- on-device
- video
- text-to-video
- image-to-video
- vae
- diffusion
---

> **Canonical:** [`kevinqz/LingBot-Video-Dense-1.3B-CoreAI`](https://huggingface.co/kevinqz/LingBot-Video-Dense-1.3B-CoreAI) — source of truth. 

# LingBot-Video Dense 1.3B (fabric)

An Apple Core AI conversion of the **VAE decoder** from
[robbyant/lingbot-video-dense-1.3b](https://huggingface.co/robbyant/lingbot-video-dense-1.3b) — the
`AutoencoderKLWan` video autoencoder's decode path, mapping a **video latent** to
**pixel frames**. Produced by [coreai-fabric](https://github.com/kevinqz/coreai-fabric/blob/main/recipes/lingbot-video-dense-1.3b.yaml) and indexed by
[coreai-catalog](https://github.com/kevinqz/coreai-catalog).

> **VAE decoder, not the full video pipeline.** A video diffusion model is four
> separable blocks — text encoder, VAE encoder, denoising DiT, and this VAE
> decoder. This asset is ONLY the decoder (latent → pixels). The **host owns** the
> text encoder, the DiT few-step denoise loop, latent un-normalization
> (`latents_mean`/`latents_std`), frame assembly, and — for multi-chunk streaming —
> the causal `feat_cache`. It does not, by itself, generate video from a prompt.

## Model facts

| Field | Value |
|---|---|
| Parameters (upstream) | 1.3B |
| Architecture | diffusion |
| Capabilities | text-to-video |
| Deployable core | AutoencoderKLWan VAE decoder (latent → frames) |
| Decoded frame shape | 1×3×1×480×832 |
| Quantization / precision | none / float32 |
| On-disk size | 273 MB |
| Asset kind | single-graph VAE decoder (first-chunk decode) |
| assetVersion | 2.0 |


## Use it — this needs host code you supply

The bundle is a single static-size graph: `z [1,16,T,H/8,W/8]` in → `frames
[1,3,Tp,H,W]` out (spatial 8× / temporal 4× upsampling, first-chunk decode).
**You supply** the DiT denoise loop that produces the latent, the latent
un-normalization, and frame assembly in your host code (Swift or Python).

```bash
pip install coreai-catalog && coreai-catalog install lingbot-video-dense-1.3b
```

## Requirements

- **Deployment: macOS 27.0+ / iOS 27.0+, Xcode 27+.** The asset serializes with `minimum_os v27`,
  so the on-device Swift runtime requires macOS/iOS 27+. A Mac on macOS 26 can
  convert and inspect it but not run it on-device.
- Apple Silicon.

## Verification (output parity)

- **Gate A (structure): passed** — the bundle's layout + metadata were
  validated; the graph loads.
- **Gate B — graph_output_cosine: 1.000000 min output cosine** (median 1.000000) vs the fp32 torch VAE decoder over 8 seeded latents, measured on apple_silicon. Certifies the export decodes the SAME pixels as the source VAE — a conversion-fidelity metric, not end video quality.
- This certifies the export is **numerically faithful to the source VAE decoder** — it
  does **NOT** certify end video quality. Reproduce with `coreai-fabric verify`.

## Provenance

| Field | Value |
|---|---|
| Base model | [robbyant/lingbot-video-dense-1.3b](https://huggingface.co/robbyant/lingbot-video-dense-1.3b) @ `f9789a7d9b4772a47aba62d4eb5282ddefd1da21` |
| Converted by | `models/lingbotvideo/export.py` (version not reported) |
| Recipe | [lingbot-video-dense-1.3b](https://github.com/kevinqz/coreai-fabric/blob/main/recipes/lingbot-video-dense-1.3b.yaml) (recipe_source: fabric) |
| Precision / quantization | float32 / none |
| Conversion date | 2026-07-09 |

Machine-readable, in this repo:
[`parity-report.json`](./parity-report.json) ·
[`reproduce-manifest.json`](./reproduce-manifest.json) · [`LICENSE`](./LICENSE).

## License and attribution

Weights licensed **apache-2.0** — see the bundled `LICENSE`. This artifact is a **converted derivative** of the base VAE: its
weights were converted to Apple Core AI format. The conversion itself is
community work.

## Links

- **Base model:** [robbyant/lingbot-video-dense-1.3b](https://huggingface.co/robbyant/lingbot-video-dense-1.3b)
- **Reproduce:** [recipe `lingbot-video-dense-1.3b`](https://github.com/kevinqz/coreai-fabric/blob/main/recipes/lingbot-video-dense-1.3b.yaml)
- **Index:** [coreai-catalog](https://github.com/kevinqz/coreai-catalog)
- [HF Collection](https://huggingface.co/collections/kevinqz/coreai-apple-on-device-6a4879f21c7e1a87c99bcf5a)


## The on-device Core AI ecosystem

- [coreai-fabric](https://github.com/kevinqz/coreai-fabric) — the reproducible
  recipe → `.aimodel` pipeline that produced this asset.
- [coreai-catalog](https://github.com/kevinqz/coreai-catalog) — the index of Core
  AI models with provenance and integration snippets.
- [apple/coreai-models](https://github.com/apple/coreai-models) — Apple's official
  exporters and runtimes.

## Not affiliated with Apple

Community conversion. Not produced, hosted, or endorsed by Apple. Apple and Core
AI are trademarks of Apple Inc., used here only to describe the target
runtime/format.