Instructions to use tencent/HY-MT1.5-7B-GPTQ-Int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/HY-MT1.5-7B-GPTQ-Int4 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="tencent/HY-MT1.5-7B-GPTQ-Int4")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tencent/HY-MT1.5-7B-GPTQ-Int4") model = AutoModelForCausalLM.from_pretrained("tencent/HY-MT1.5-7B-GPTQ-Int4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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| Kazakh | kk | 哈萨克语 |
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| Mongolian | mn | 蒙古语 |
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| Uyghur | ug | 维吾尔语 |
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| Cantonese | yue | 粤语 |
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| Kazakh | kk | 哈萨克语 |
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| Mongolian | mn | 蒙古语 |
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| Uyghur | ug | 维吾尔语 |
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| Cantonese | yue | 粤语 |
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Citing HY-MT1.5:
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```bibtex
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@misc{hy-mt1.5,
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title={HY-MT1.5 Technical Report},
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author={Mao Zheng and Zheng Li and Tao Chen and Mingyang Song and Di Wang},
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year={2025},
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eprint={2512.24092},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2512.24092},
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}
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```
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