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Use HF papers (#38184)

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* Use hf papers

* Hugging Face papers

* doi to hf papers

* style
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Quentin Gallouédec
2025-06-13 13:07:09 +02:00
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docs/source/en/model_doc/bitnet.md
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Trained on a corpus of 4 trillion tokens, this model demonstrates that native 1-bit LLMs can achieve performance comparable to leading open-weight, full-precision models of similar size, while offering substantial advantages in computational efficiency (memory, energy, latency).
➡️ **Technical Report:** [BitNet b1.58 2B4T Technical Report](https://arxiv.org/abs/2504.12285)
➡️ **Technical Report:** [BitNet b1.58 2B4T Technical Report](https://huggingface.co/papers/2504.12285)
➡️ **Official Inference Code:** [microsoft/BitNet (bitnet.cpp)](https://github.com/microsoft/BitNet)