{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Programming Tech Brief By HackerNoon","title":"Orca 2: Enhancing Reasoning in Smaller Language Models - Example from Benchmarks and Output","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/c5fc6dc8\"></iframe>","width":"100%","height":180,"duration":107,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/orca-2-enhancing-reasoning-in-smaller-language-models-example-from-benchmarks-and-output.\nOrca 2 enhances small language models' reasoning by teaching diverse strategies for tasks, outperforming models up to 10x larger in complex benchmarks.\nCheck more stories related to programming at: https://hackernoon.com/c/programming.\n            You can also check exclusive content about #language-models, #orca-2, #reasoning-techniques, #machine-learning, #small-models, #imitation-learning, #ai-benchmarks, #model-training,  and more.\nThis story was written by: @textmodels. Learn more about this writer by checking @textmodels's about page,\n            and for more stories, please visit hackernoon.com.\nTeaching Orca 2 to be a Cautious Reasoner is based on the work of Arindam Mitra, Luciano Del Corro, Shweti Mahajan, Andres Codas, Guoqing Zheng, Corby Rosset, Hamed Khanpour, and Ahmed Awadall.","thumbnail_url":"https://img.transistorcdn.com/KhCapPSRkLGL2Xw8888yuChkNRWthaKapLYTvNdu4W4/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMTY2LzE2ODM1/ODIzMzAtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}