How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUF# Run inference directly in the terminal:
llama cli -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUFUse pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUF# Run inference directly in the terminal:
./llama-cli -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUFBuild from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUF# Run inference directly in the terminal:
./build/bin/llama-cli -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUFUse Docker
docker model run hf.co/zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUFQuick Links
Hy-MT2-1.8B-1.25Bit-GGUF
STQ1_0 quantized GGUF of Tencent's Hy-MT2 1.8B translation model for on-device inference.
Base Model
- Model: Hy-MT2 1.8B (33-language translation)
- Provider: Tencent
- Source: https://huggingface.co/tencent/Hy-MT2-1.8B
- License: Apache 2.0
- Parameters: 1.8B
Quantization Details
- Format: STQ1_0 (1.25-bit Sherry quantization)
- GGUF Size: ~441 MB
- Original source: AngelSlim/Hy-MT2-1.8B-1.25Bit-GGUF (commit 5946a42)
- Hosted by: Zanish Labs / Voco
Runtime
- Compatible with llama.cpp (CPU/NEON)
- Requires STQ1_0 generic kernel dispatch on Apple Silicon (NEON kernel broken)
- Tested on Voco iOS app (llama.cpp PR #22836)
Attribution
This is a quantized derivative. The original model was created by Tencent. See LICENSE for full license text.
Links
- Original model: https://huggingface.co/tencent/Hy-MT2-1.8B
- Voco app: https://github.com/Zane-dev16/Voco
- llama.cpp: https://github.com/Zane-dev16/llama.cpp-voco
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Hardware compatibility
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Model tree for zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUF
Base model
tencent/Hy-MT2-1.8B
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUF# Run inference directly in the terminal: llama cli -hf zanish-labs/Hy-MT2-1.8B-1.25Bit-GGUF