Download the model via (after installing pip install huggingface_hub hf_transfer ). You can choose MXFP4_MOE or other quantized versions like UD-Q4_K_XL . We recommend using at least 2-bit dynamic quant UD-Q2_K_XL to balance size and accuracy. If downloads get stuck, see: Hugging Face Hub, XET debugging
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The magic is in that codify step. LLMs are stateless. If they re-introduce a dependency you explicitly removed yesterday, they'll do it again tomorrow unless you tell them not to. The most common way to close that loop is updating your CLAUDE.md (or equivalent rules file) so the lesson is baked into every future session. A word of caution: the instinct to codify everything into your rules file can backfire (too many instructions is as good as none). The better move is to create a setting where the LLM can easily discover useful context on its own, for example by maintaining an up-to-date docs/ folder (more on this in Level 7).，这一点在新收录的资料中也有详细论述
（六）扎实推进“四个机关”建设。坚持党中央集中统一领导，持续强化党的创新理论武装。认真开展树立和践行正确政绩观学习教育，坚持为人民出政绩、以实干出政绩，从实际出发、按规律办事，不断提升工作质效。增强人大新闻宣传的传播力、影响力。运用数字化、智能化手段提高人大工作水平。落实全面从严治党政治责任。加强与地方人大的工作联系和协同，共同提高新时代人大工作水平。，推荐阅读新收录的资料获取更多信息
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