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<br>Recently, I showed how to easily run distilled variations of the [DeepSeek](https://herobe.com) R1 design in your area. A distilled model is a compressed variation of a bigger language design, where understanding from a larger design is transferred to a smaller one to [reduce resource](http://supervipshop.net) use without losing too much performance. These models are based upon the Llama and Qwen architectures and be available in variations varying from 1.5 to 70 billion [parameters](https://ie3i.com).<br> |
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<br>Some explained that this is not the [REAL DeepSeek](https://www.impresalikeagirl.it) R1 which it is [impossible](http://catalog.flexcom.ru) to run the full model in your area without several hundred GB of memory. That seemed like a difficulty - I believed! First Attempt - Heating Up with a 1.58 bit Quantized Version of [DeepSeek](https://andhara.com) R1 671b in Ollama.cpp<br> |
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<br>The [developers](http://agentevoip.net) behind [Unsloth dynamically](https://funfurpaws.com) [quantized DeepSeek](http://www.codeent.com.my) R1 so that it could work on as low as 130GB while still gaining from all 671 billion specifications.<br> |
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<br>A quantized LLM is a LLM whose specifications are kept in lower-precision formats (e.g., 8-bit or [smfsimple.com](https://www.smfsimple.com/ultimateportaldemo/index.php?action=profile |
