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Wop

wop
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https://bench-labs-org.github.io

AI & ML interests

AI research AGI

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reacted to raincandy-u's post with šŸ‘ about 15 hours ago
20K parameters can tell a story. šŸš€ šŸ¤— We trained a ~20k-parameter Transformer that can actually write stories! https://huggingface.co/raincandy-u/MacroStories ā†’ ~50Ɨ smaller than the 1M-parameter TinyStories model ā†’ ~3,000Ɨ smaller than AlexNet ā†’ 81 KB in FP32 yayyy the whole model. ą«® Ė¶įµ” įµ• įµ”Ė¶ įƒ She has a 32-dimensional hidden state, a 378-token vocabulary, and just one decoder block ā€” recurrently applied 4 times with shared weights. Despite having only 19,969 parameters, she can maintain a simple narrative across 100ā€“300 words: establish a goal, encounter a problem, take relevant actions, and reach an outcome. She runs extremely fast on CPU ā€” no GPU required. The entire model is tiny enough to load almost instantly! ā˜ŗļø
reacted to raincandy-u's post with šŸ”„ about 15 hours ago
20K parameters can tell a story. šŸš€ šŸ¤— We trained a ~20k-parameter Transformer that can actually write stories! https://huggingface.co/raincandy-u/MacroStories ā†’ ~50Ɨ smaller than the 1M-parameter TinyStories model ā†’ ~3,000Ɨ smaller than AlexNet ā†’ 81 KB in FP32 yayyy the whole model. ą«® Ė¶įµ” įµ• įµ”Ė¶ įƒ She has a 32-dimensional hidden state, a 378-token vocabulary, and just one decoder block ā€” recurrently applied 4 times with shared weights. Despite having only 19,969 parameters, she can maintain a simple narrative across 100ā€“300 words: establish a goal, encounter a problem, take relevant actions, and reach an outcome. She runs extremely fast on CPU ā€” no GPU required. The entire model is tiny enough to load almost instantly! ā˜ŗļø
new activity about 15 hours ago
mlx-community/clef-flash-4bit:Add decision-model tag
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