Instructions to use litert-community/Hy-MT2-1.8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use litert-community/Hy-MT2-1.8B with LiteRT-LM:
# LiteRT-LM runs on various platforms (Android, iOS, Windows, Linux, macOS, IoT, Web/WASM) # and supports many APIs (C++, Python, Kotlin, Swift, JavaScript, Flutter). # For platform-specific integration guides, please refer to the official developer website: # https://ai.google.dev/edge/litert-lm # To try LiteRT-LM, the easiest way is to use our CLI tool. # 1. Install the LiteRT-LM CLI tool: pip install -U litert-lm # 2. Download and run this model locally: # See: https://ai.google.dev/edge/litert-lm/cli # A single .litertlm file in the repo is picked automatically; otherwise the CLI asks which one to run # (or pass its name right after the repo id). litert-lm run \ --from-huggingface-repo=litert-community/Hy-MT2-1.8B \ --prompt="Write me a poem"
- LiteRT
How to use litert-community/Hy-MT2-1.8B with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Chat template: accept the 0.18 content-parts form (string form unchanged); weights, tokenizer and executor metadata byte-identical
Browse files- Hy-MT2-1.8B_int8.litertlm +1 -1
- README.md +2 -0
- litertlm_manifest.json +3 -3
Hy-MT2-1.8B_int8.litertlm
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 1815622960
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version https://git-lfs.github.com/spec/v1
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oid sha256:529e6d378df5869d89a5a08717c06604105a32d8a4dab4800175d6baabc4da50
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size 1815622960
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README.md
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@@ -64,6 +64,8 @@ Hy-MT2-1.8B is Tencent's "fast-thinking" multilingual **translation model**: 33
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| `Hy-MT2-1.8B_int8.litertlm` | export-time dynamic int8 (linears + embedding) | 1.82 GB |
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## Correctness
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All numbers below were measured on **this exact file** (litert-lm 0.16.0, Apple M4 Max).
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| `Hy-MT2-1.8B_int8.litertlm` | export-time dynamic int8 (linears + embedding) | 1.82 GB |
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2026-09-21: chat template updated to accept the 0.18 content-parts form (string form unchanged); weights, tokenizer and executor metadata byte-identical.
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## Correctness
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All numbers below were measured on **this exact file** (litert-lm 0.16.0, Apple M4 Max).
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litertlm_manifest.json
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{
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"manifest_schema": "0.1.2",
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"repo": "litert-community/Hy-MT2-1.8B",
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"generated": "2026-09-
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"generator": "make_manifest.py",
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"model": {
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"display_name": "Hy-MT2-1.8B",
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"variants": [
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{
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"file": "Hy-MT2-1.8B_int8.litertlm",
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"sha256": "
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"size_bytes": 1815622960,
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"sections": [
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{
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"type": "LlmMetadataProto",
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"size_bytes":
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},
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{
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"type": "HF_Tokenizer_Zlib",
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{
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"manifest_schema": "0.1.2",
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"repo": "litert-community/Hy-MT2-1.8B",
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"generated": "2026-09-22",
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"generator": "make_manifest.py",
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"model": {
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"display_name": "Hy-MT2-1.8B",
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"variants": [
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{
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"file": "Hy-MT2-1.8B_int8.litertlm",
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"sha256": "529e6d378df5869d89a5a08717c06604105a32d8a4dab4800175d6baabc4da50",
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"size_bytes": 1815622960,
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"sections": [
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{
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"type": "LlmMetadataProto",
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"size_bytes": 1056
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},
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{
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"type": "HF_Tokenizer_Zlib",
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