Hy-MT2 keeps gaining momentum.
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Hy-MT2 keeps gaining momentum. Since its open-source release in May: → 700K+ downloads 🌟 → Hy-MT2-1.8B reached #1 on the Hugging Face trending, with 30B-A3B reaching #4 🥇 → 70+ verified product and project integrations 💻 → Broader Hy-MT ecosystem support across Apple MLX-LM, Microsoft ONNX Runtime, NVIDIA NeMo, LLaMA-Factory, and more 👯 → Real-world adoption, including real-time multilingual translation of livestream comments on Bilibili 📺 And now, Hy-MT2-30B-A3B is officially available in GGUF format—addressing one of the community’s most-requested deployment needs and making local inference easier. Ready to run Hy-MT2-30B-A3B locally? Try the new GGUF release: https://t.co/adbLlTVV7I Explore Hy-MT2: HuggingFace：https://t.co/4J8gzMcENW Modelscope：https://t.co/xh5vEYk9zQ Github：https://t.co/EekzbAcLZp #TencentHy #HyMT2 #OpenSource
Context
Tencent's Hy-MT2 update adds an official GGUF release of its 30B-A3B translation model, giving developers a packaged route to local . The model page documents loading it with llama.cpp, a local model runtime. This makes the deployment change concrete: users can obtain the supplied files and run the translation model through a compatible runtime. The announcement presents this as a response to community requests.
- inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
- open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
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