[{"data":1,"prerenderedAt":33},["ShallowReactive",2],{"maker-kossisoroyce":3},[4],{"id":5,"name":6,"line":7,"ai":8,"cat":9,"year":10,"points":11,"comments":12,"rec":13,"s":14,"top":15,"kw":16,"maker":22,"domain":23,"tier":24,"attempts":14,"strip":25,"url":26,"mix":27,"praise":30,"objection":31,"sub":32},47212576,"Timber","Ollama for classical ML models, 336x faster than Python",false,"ai",2026,207,33,"debated",0,7,[17,18,19,20,21],"classical ml","model serving","scikit-learn inference","onnx","ml deployment","kossisoroyce","github.com","notable","3000010030301033015050503515051000","https:\u002F\u002Fgithub.com\u002Fkossisoroyce\u002Ftimber",[28,28,14,29],6,5,"Good concept and timely for classical ML serving","Ollama is a weak analogy; classical ML models are narrow and not interchangeable like LLMs","classical ml inference",1794036822783]