Type a word or a sentence and get the emoji that fits. Emo is tuned for to-dos, calendar entries, notes, and message drafts across **22 languages** (including CJK, Arabic, Thai, Hindi, and more). The model and tokenizer together are small (**5MB** on Apple via Core ML, **11MB** via LiteRT elsewhere) and runs in well under 2ms on device. > `"Dentist appointment"` → 🦷 · `"réserver un vol pour Tokyo"` → ✈️ · `"犬の散歩"` → 🐕 · `"จองโรงแรม"` → 🏨 - **Live demo:** desert-ant-labs/emo-demo: type a phrase, get emojis, fully in your browser. **Swift** (requirements)

Text analysis

Input Text→ Output Text

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eye

desert-ant-labs

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Image classification

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gist

desert-ant-labs

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Text analysis

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moderator

desert-ant-labs

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Image classification

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redact

desert-ant-labs

Strip names, addresses, emails, phone numbers, cards, IBANs and national IDs out of text before it leaves the device, across **27 languages** (see Languages). A token classifier plus a deterministic layer for structured IDs. The deployable model is **11.6MB** (4-bit Core ML on Apple) or **24.5MB** (int8 LiteRT `.tflite` on Android, Linux and the web). > `"Call Anna Kovács at anna@example.hu, IBAN GB29NWBK60161331926819"` → > `"Call [GIVEN_NAME] [SURNAME] at [EMAIL], IBAN [BANK_ACCOUNT]"` `GIVEN_NAME`, `SURNAME`, `STREET_NAME`, `BUILDING_NUMBER`, `SECONDARY_ADDRESS`, `CITY`, `STATE`, `ZIP_CODE`, `EMAIL`, `PHONE`, `CREDIT_CARD`, `BANK_ACCOUNT`, `ROUTING_NUMBER`, `IP_ADDRESS`, `URL`, `GOVERNMENT_ID`, `PASSPORT`, `DRIVERS_LICENSE`, `TAX_ID`, `SSN`.

Text analysis

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shapes

desert-ant-labs

Turn a rough circle drawing into a clean shape, with fitted vector geometry ready to snap to. Built for PencilKit-style "smart shapes": draw, pause, and the rough stroke becomes a crisp shape. The model is tiny (**200KB** Core ML, **1.3MB** LiteRT) and runs in a few milliseconds on device. `line`, `rectangle`, `triangle`, `ellipse`, `star`, plus `none` (the reject class: scribbles, partial shapes, and other non-shape strokes). Squares and circles are covered by `rectangle` and `ellipse` (snapped when near-regular). 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: .

Image classification

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title

desert-ant-labs

On-device titles and descriptions: a short factual title and a one- to two-sentence description for any passage of text. Get a title and a one or two sentence description for any passage of text, on device. Title is fine-tuned on transcript clips, but it works on any prose. The register is deliberately plain, with no emoji, no hashtags and no clickbait, and a description identifies *this* passage rather than its topic.

Text generation

Input Text→ Output Text

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uhm

desert-ant-labs

Find every "uh", "um" and "hmm" in an audio file, down to 20ms. Uhm runs on device, does not require ASR, and is trained on English with acoustic transfer to Spanish, French, German, and Dutch. `uhm.mlmodelc/` is a compiled Core ML model directory. The Swift SDK downloads it with the Hugging Face Hub snapshot API, so only changed files are re-fetched on model updates. `uhm.tflite` is what the Kotlin and JavaScript SDKs download; it is converted from `uhm.onnx` and matches it at 99.7 to 100% per-frame argmax. The shipped model is a DistilHuBERT fine-tune, the smaller and more precise Uhm runtime model; the older HuBERT-base tier is no longer published.

Audio processing

Input Audio→ Output Not verified

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voz

desert-ant-labs

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Speech recognition

Input Audio→ Output Text

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who

desert-ant-labs

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Category pending

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COST EXPLORER

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Cost analysis

Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

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