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README.md
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<h1 style="margin-top: 0rem;">🌙 Kimi K2 Usage Guidelines</h1>
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It is recommended to have at least 128GB unified RAM memory to run the small quants. With 16GB VRAM and 256 RAM, expect 5+ tokens/sec.
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For best results, use any 2-bit XL quant or above.
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Set the temperature to 0.6 recommended) to reduce repetition and incoherence.
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- For complete detailed instructions, see our guide: [docs.unsloth.ai/basics/kimi-k2](https://docs.unsloth.ai/basics/kimi-k2)
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<picture>
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<h1 style="margin-top: 0rem;">🌙 Kimi K2 Usage Guidelines</h1>
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- To run, you must use llama.cpp [PR #14654](https://github.com/ggml-org/llama.cpp/pull/14654) or [our llama.cpp fork](https://github.com/unslothai/llama.cpp) (easier)
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- For complete detailed instructions, see our guide: [docs.unsloth.ai/basics/kimi-k2](https://docs.unsloth.ai/basics/kimi-k2)
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It is recommended to have at least 128GB unified RAM memory to run the small quants. With 16GB VRAM and 256 RAM, expect 5+ tokens/sec.
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For best results, use any 2-bit XL quant or above.
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Set the temperature to 0.6 recommended) to reduce repetition and incoherence.
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<div align="center">
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<picture>
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