├── llm.mnn              # Model structure (576 KB)
├── llm.mnn.weight       # Quantized weights (4.47 GB)
├── tokenizer.txt        # Tokenizer vocabulary
├── llm_config.json      # MNN runtime config
├── config.json          # Model config
├── model_info.json      # Model metadata
└── export_args.json     # Conversion parameters

Usage

With MNN LLM Demo

bash

# Clone MNN and build llm_demo
git clone https://github.com/alibaba/MNN.git
cd MNN && mkdir build && cd build
cmake .. -DMNN_BUILD_LLM=ON -DMNN_LOW_MEMORY=ON
make -j8 llm_demo

# Run inference
cd /path/to/HY-MT1.5-7B-MNN
./llm_demo ./

Example

User: Translate into English: 今天天氣很好
A: The weather is very nice today.

Prompt Templates

# Basic translation
Translate into {language}:
{text}

# With terminology
Translate into {language}, using terms: {terms}
{text}

# With context
Context: {context}
Translate into {language}:
{text}

Performance

Metric	Value
Model Load Time	~3.5s
Inference Speed	20-30 tokens/s
Target Device	Apple Silicon Mac

Conversion Info

Tool: MNN llmexport.py
MNN Version: 3.0.0
Conversion Date: 2025-12-31
Source Format: HuggingFace safetensors

Related Models

HY-MT1.5-1.8B-MNN - Smaller version for iOS devices
Hunyuan-MT-7B-MNN - Original WMT25 version

License

This model inherits the license from the original HY-MT1.5-7B model.

Acknowledgments

Tencent Hunyuan Team for the original model
Alibaba MNN Team for the inference framework

wangjazz/Hunyuan-MT1.5-7B-MNN

HY-MT1.5-7B-MNN

Model Description

Quantization Details

Hardware Acceleration

Files

Usage

With MNN LLM Demo

Example

Prompt Templates

Performance

Conversion Info

Related Models

License

Acknowledgments

wangjazz/
Hunyuan-MT1.5-7B-MNN