Hy-MT2-1.8B-4bit (MLX)

This is a 4-bit MLX quantized version of tencent/Hy-MT2-1.8B, optimized for Apple Silicon (M1/M2/M3/M4) via the MLX framework.

Model Details

• Base model: tencent/Hy-MT2-1.8B
• Architecture: HunYuanDenseV1ForCausalLM (Hunyuan Dense V1, 1.8B parameters)
• Quantization: 4-bit, group size 64, affine mode
• Format: MLX safetensors
• File size: ~1.0 GB (model.safetensors)
• Task: Translation across 35+ languages

Conversion

This model was converted with mlx-lm 0.31.3:

mlx_lm.convert \
    --hf-path tencent/Hy-MT2-1.8B \
    --mlx-path Hy-MT2-1.8B-4bit \
    --quantize \
    --q-bits 4 \
    --q-group-size 64

Usage with mlx-lm

Install:

pip install mlx-lm

Inference (uses the bundled chat_template.jinja from the original repo):

from mlx_lm import load, generate

model, tokenizer = load("illitan/Hy-MT2-1.8B-4bit")

messages = [
    {"role": "user", "content": "Translate the following text to Chinese: 'Hello, how are you today?'"}
]

prompt = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
)

response = generate(
    model,
    tokenizer,
    prompt=prompt,
    max_tokens=256,
    verbose=True,
)
print(response)

Supported Languages

Same coverage as the base model — 35+ languages including Chinese, English, French, Portuguese, Spanish, Japanese, Turkish, Russian, Arabic, Korean, Thai, Italian, German, Vietnamese, Malay, Indonesian, Tagalog, Hindi, Polish, Czech, Dutch, Khmer, Burmese, Persian, Gujarati, Urdu, Telugu, Marathi, Hebrew, Bengali, Tamil, Ukrainian, Tibetan, Kazakh, Mongolian, and Uyghur.

See the base model card for full translation direction coverage.

License

This model is released under the Tencent HY Community License Agreement (inherited from the base model). See the full license text at tencent/Hy-MT2-1.8B/LICENSE.txt.

Important geographic restriction

The Tencent HY Community License explicitly prohibits use, reproduction, modification, and distribution of the model (including derivatives such as this quantization) within the European Union.

If you are located in the EU, you are not permitted to download or use this model. Please review the upstream license before any commercial or research use.

Acknowledgements

• Tencent for the original Hy-MT2-1.8B model.
• Apple MLX team and mlx-lm for the on-device inference stack.