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README.md
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
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# Information
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Advanced, high-quality and lite reasoning for a tiny size that you can run on your phone.
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# Which quant is right for you?
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<output>3
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</output><|im_end|>
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```
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# system prompt
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(important to ensure it would always think, output).
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```
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
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# Information
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Advanced, high-quality and **lite** reasoning for a tiny size that you can run on your phone.
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At original quality, it runs at ~400 tokens/second on a single H100 Nvidia GPU from Friendli.
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Trained similarly to Deepseek R1, we used Smollm2 as a base model, then we've SFT fine tuned on reasoning using our own private superthoughts instruct dataset which includes a mix of code, website generation, day-to-day chats, math and counting problems. And then we modified the tokenizer slightly, after the SFT fine tuning we used GRPO to further amplify it's mathematics & problem solving abilities.
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# Which quant is right for you?
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<output>3
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</output><|im_end|>
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```
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We reccomend to use a low temperatures as higher values may cause it to not think.
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# system prompt
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(important to ensure it would always think, output).
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```
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