Downloads · 30 days
270
72% of all-time downloads
desert-ant-labs/clips
clips is a text ranking model from desert-ant-labs. Use it for the text ranking task on the model card, and read the license before you ship it in a product. It is set up for litert. The card lists the license as other.
Create short videos and highlight clips.
Downloads · 30 days
270
72% of all-time downloads
All-time downloads
375
Public
Repo size
854 MB
Likes
17
Trending 1
Click a slice to open those files.
.tflite566 MB · 66%
From the Hugging Face model README
Create short videos and highlight clips.
Short clips and highlights from talking video and audio: podcasts, interviews, meetings. On-device.
| Platforms | iOS, macOS, tvOS, visionOS, Linux, Windows |
| Weights | v0.1.0 |
Swift (requirements)
.package(url: "https://github.com/Desert-Ant-Labs/desert-ant-core.git", from: "3.6.0")
Then add the Clips product to your target.
Point Clips at a transcript and get the moments worth cutting, ranked best first and never overlapping. Nothing is uploaded, so clipping a back catalogue costs the same as clipping one video.
284MB as a single int8 Core ML package on Apple platforms, or two 283MB LiteRT files elsewhere. 100 languages.
Clips carry no title. Pairing them with words is a separate model,
desert-ant-labs/title.
There's no context window. Clips never reads a transcript whole: sentences run through the selector in batches of 16 and each candidate clip is scored on its own, so length is bounded by time rather than by a token limit. The longest we've run is an 835 sentence podcast.
| transcript | iPhone 17 Pro | iPhone 15 Pro |
|---|---|---|
| 404 sentences, 25 minutes of video, 12 clips | 9.19s | 10.22s |
| 57 sentences | 2.23s | |
| per candidate, encoder only | 2.78ms | 3.13ms |
Measured on device at batch 16, pinned to .cpuAndNeuralEngine.
| File | Format | Size | Contents |
|---|---|---|---|
clips.mlmodelc/ | Compiled Core ML, int8 per-channel | 284MB | Multifunction package. Function select: ids, mask, disc to saliency, start_p, end_p. Function score: ids, mask to score |
clips-selector.tflite | LiteRT, int8 weight-only | 283MB | The selector, for Android, Linux and Windows |
clips-scorer.tflite | LiteRT, int8 weight-only | 283MB | The scorer, for Android, Linux and Windows |
clip_tokenizer.bin | Unigram tokenizer | 4MB | Tokenizer pieces and scores, in the compact binary the runtimes read |
clips_meta.json | JSON | tiny | Graph widths, input roles and feature order a runtime needs |
On Apple platforms both graphs live in one Core ML package with the shared weights stored once. LiteRT has no equivalent packaging, so the other platforms ship two files.
The selector graph is 128 tokens wide, the scorer 256, both at a fixed batch of 16 sentences. A sentence longer than 64 tokens is truncated before it reaches the selector.
Set MLModelConfiguration.functionName to select or score. A path names the package, not the
graph, and Core ML loads the default function silently, so without it both halves of your pipeline
run the selector.
The LiteRT graphs take int64 ids and mask, and name their inputs positionally, args_0
upward, so clips_meta.json carries the mapping. Feed ids and mask swapped and the graph returns finite, plausibly scaled numbers
and a pipeline that quietly builds the wrong pool.
Clip.score runs 1 to 5 and is not calibrated between videos. Threshold on percentile instead.
An absolute cut at 0.65 returns nothing on 21% of videos, and at 0.75 on half of them. Per-video
95th percentiles range from 0.33 to 0.95.
| percentile cut | clips per video | share of the video covered | use |
|---|---|---|---|
| 0.8 | 5.0 | 17% | highlights |
| 0.3 | 32.1 | 74% | auto edit |
iOS 18, macOS 15, tvOS 18, visionOS 2, watchOS 11. Android, Linux and Windows through LiteRT, driven directly rather than through the SDK.
<!-- card-footer:start (generated from manifest.json, edit above this block) -->Desert Ant Labs Source-Available License. Free for most apps, and a commercial license is required at scale. Full terms are at the link. Licensing: [email protected].
@software{clips_2026,
title = {Clips: Short clips and highlights from talking video and audio: podcasts, interviews, meetings. On-device},
author = {Desert Ant Labs},
year = {2026},
url = {https://huggingface.co/desert-ant-labs/clips},
}
© 2026 Desert Ant Labs · https://desertant.com
<!-- card-footer:end -->