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README.md
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### <font color=red>Nanbeige/Nanbeige4.1-3B </font> (4 billion model, "marketed" as 3B billions), with 92% HumanEval accuracy in Python
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- Time to finish 160 questions from HumanEval: 22263.80s --- MORE THAN SIX HOURS!!! (in a RTX 5060 ti 16gb)
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### <font color=red>Nerdsking/nerdsking-python-coder-3B-i</font>, with 88,41% HumanEval accuracy in Python
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- Time to finish 160 questions from HumanEval: 210.51s --- THREE MINUTES AND HALF (in a RTX 5060 ti 16gb)
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<b><i><font color=red>Lesson: Anyone can create a bigger model with an "eternal loop" to solve problems by randomly trying all possible variables. That is not "intelligence", that's
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### <font color=red>Nanbeige/Nanbeige4.1-3B </font> (4 billion model, "marketed" as 3B billions), with 92% HumanEval accuracy in Python
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- Time to finish 160 questions from HumanEval: 22263.80s --- MORE THAN SIX HOURS!!! (in a RTX 5060 ti 16gb)
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### <font color=red>Nerdsking/nerdsking-python-coder-3B-i</font>, (real 3 billion model) with 88,41% HumanEval accuracy in Python
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- Time to finish 160 questions from HumanEval: 210.51s --- THREE MINUTES AND HALF (in a RTX 5060 ti 16gb)
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<b><i><font color=red>Lesson: Anyone can create a bigger model with an "eternal loop" to solve problems by randomly trying all possible variables. That is not "intelligence", that's
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