| --- |
| license: mit |
| base_model: TensorForger/RIFE-safetensors |
| pipeline_tag: image-to-image |
| library_name: coreai |
| tags: |
| - coreai |
| - core-ai |
| - coreai-fabric |
| - aimodel |
| - coreml |
| - apple |
| - apple-silicon |
| - on-device |
| - frame-interpolation |
| - video |
| - image-to-image |
| --- |
| |
| > **Canonical:** [`kevinqz/RIFE-Frame-Interpolation-CoreAI`](https://huggingface.co/kevinqz/RIFE-Frame-Interpolation-CoreAI) — source of truth. |
|
|
| # RIFE Frame Interpolation (fabric) |
|
|
| An Apple Core AI conversion of |
| [TensorForger/RIFE-safetensors](https://huggingface.co/TensorForger/RIFE-safetensors) — a **frame |
| interpolation** network that takes two stacked RGB frames and synthesizes the |
| **intermediate frame** between them. Produced by [coreai-fabric](https://github.com/kevinqz/coreai-fabric/blob/main/recipes/rife-4-interp.yaml) and |
| indexed by [coreai-catalog](https://github.com/kevinqz/coreai-catalog). |
|
|
| > **Frame interpolation, not a generator.** This is a single-forward interpolator — two frames in, one synthesized frame at t=0.5 out. No temporal model, no audio. The **host owns** frame decode/encode and resizing each frame to a multiple of 32 before feeding the graph. |
|
|
| ## Model facts |
|
|
| | Field | Value | |
| |---|---| |
| | Parameters | 0.01B | |
| | Architecture | cnn/transformer | |
| | Capabilities | super-resolution | |
| | Input | 1×6×256×256 — concat(img0[:3], img1[3:]) in [0,1] | |
| | Output frame | 1×3×256×256 @ t=0.5 | |
| | Quantization / precision | none / float32 | |
| | On-disk size | 17 MB | |
| | Asset kind | single-graph frame interpolator (two frames -> middle frame) | |
| | assetVersion | 2.0 | |
|
|
|
|
| ## Use it — this needs host code you supply |
|
|
| The bundle is a single static-size graph: `frames` (1×6×256×256, `img0` and `img1` concatenated on the channel axis, RGB in [0,1]) in → the interpolated `frame` (1×3×256×256) out. **You supply** the video demux/mux, frame resizing, and any multi-t or recursive-interpolation loop in your host code (Swift or Python). |
|
|
| ```bash |
| pip install coreai-catalog && coreai-catalog install rife-4-interp |
| ``` |
|
|
| ## 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 reference network over 8 seeded frame pairs, measured on apple_silicon. Certifies the export computes the SAME output as the source — a conversion-fidelity metric, not task accuracy. |
| - This certifies the export is **numerically faithful to the source network** — it |
| does **NOT** certify perceptual interpolation quality on your footage. Reproduce |
| with `coreai-fabric verify`. |
| |
| ## Provenance |
| |
| | Field | Value | |
| |---|---| |
| | Base model | [TensorForger/RIFE-safetensors](https://huggingface.co/TensorForger/RIFE-safetensors) @ `78a62b7c2dd910536432d6c2c3a25e76f14fbf78` | |
| | Converted by | `models/rife/export.py` (version not reported) | |
| | Recipe | [rife-4-interp](https://github.com/kevinqz/coreai-fabric/blob/main/recipes/rife-4-interp.yaml) (recipe_source: fabric) | |
| | Precision / quantization | float32 / none | |
| | Conversion date | 2026-07-10 | |
|
|
| Machine-readable, in this repo: |
| [`parity-report.json`](./parity-report.json) · |
| [`reproduce-manifest.json`](./reproduce-manifest.json) · [`LICENSE`](./LICENSE). |
|
|
| ## License and attribution |
|
|
| Weights licensed **mit** — see the bundled `LICENSE`. This artifact is a **converted derivative** of the base model: its |
| weights were converted to Apple Core AI format. The conversion itself is |
| community work. |
|
|
| ## Links |
|
|
| - **Base model:** [TensorForger/RIFE-safetensors](https://huggingface.co/TensorForger/RIFE-safetensors) |
| - **Reproduce:** [recipe `rife-4-interp`](https://github.com/kevinqz/coreai-fabric/blob/main/recipes/rife-4-interp.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. |
|
|
