Emo

Suggest emoji faster than you can type.

Multilingual on-device emoji suggestion.

Type a word or a sentence and get the emoji that fits. Tuned for to-dos, calendar entries, notes, and message drafts across 22 languages (including CJK, Arabic, Thai, Hindi, and more). The whole thing, model and tokenizer, is 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" → 🏨

Try it

Platforms iOS, macOS, tvOS, visionOS, Android, Linux, Windows, Browser, Node
Languages 22
Weights v0.7.0

Install

Swift (requirements)

.package(url: "https://github.com/Desert-Ant-Labs/desert-ant-core.git", from: "3.1.0")

Then add the Emo product to your target.

Kotlin (requirements)

implementation("ai.desertant:emo:3.1.0")

JavaScript (requirements)

npm i @desert-ant-labs/emo @litertjs/core   # browser
npm i @desert-ant-labs/emo                  # Node, prebuilt native core

Files

File Format Size Contents
emo.tflite LiteRT / TFLite (int8) 10.2MB Runs on Android, Linux, Node, and the web (bundled by default in the Kotlin SDK; downloaded on demand by the JavaScript SDK)
emo.mlmodelc Compiled Core ML 4.6MB Ready to load on Apple platforms (used by the Swift SDK)
emo_tokenizer.bin Unigram tokenizer 750KB Tokenizer the runtime needs
emo_meta.json JSON tiny Emoji labels and runtime config

Older revisions (tags v0.6.0 and earlier) carry Emo.mlmodelc and emo.safetensors for SDK versions that predate the unified cross-platform migration.

Inputs and outputs

  • Input: a plain text string. Best on short, intent-oriented text.
  • Output: a probability distribution over the 812-emoji vocabulary; take the top-1 (or top-k). Optimized for top-1 relevance.

Languages

English, Spanish, Portuguese, French, German, Italian, Dutch, Russian, Polish, Turkish, Arabic, Chinese (Simplified & Traditional), Japanese, Korean, Hindi, Indonesian, Thai, Vietnamese, Ukrainian, Swedish, Danish, Czech.

Limitations

  • Tuned for short, intent-oriented text; long-form text produces noisier suggestions.
  • Emoji semantics are imprecise; near-ties at the top of the ranking are expected.
  • Per-language quality varies; lower-resource languages in the set are somewhat weaker.

License

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: licensing@desertant.com.

See THIRD_PARTY_NOTICES.md.

Citation

@software{emo_2026,
  title  = {Emo: Multilingual on-device emoji suggestion},
  author = {Desert Ant Labs},
  year   = {2026},
  url    = {https://huggingface.co/desert-ant-labs/emo},
}

© 2026 Desert Ant Labs · https://desertant.com

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