| import{_ as e}from"./index-D8Tp3Qg8.js";import{U as i,W as t,Y as o,k as a,Z as n,V as s,F as l,f as r,_ as p,$ as c,a2 as m,a0 as h,G as d}from"./vue-vendor-BhBNFBI8.js";import"./antd-vendor-BaRhxx_v.js";const g={class:"section open-philosophy-section unified-section-bg"},f={class:"philosophy-card-wrapper unified-card"},u={class:"philosophy-item-img"},y=["src"],v={key:0,class:"philosophy-item-title",style:{"font-size":"1.2rem","margin-top":"1rem"}},k={class:"philosophy-item-text"},C={key:0,class:"philosophy-item-title"},b=["innerHTML"],w={class:"philosophy-item-action"};const _=e({name:"OpenPhilosophySection",setup:()=>({philosophyItems:r([{title:"Chaoyue Cup: OpenSeek's Journey Beyond Co-Creation of LLM Challenge Competition",description:"\n The competition centers around three key tracks: designing effective data mixing strategies to balance diverse domains, developing optimized training strategies to improve learning efficiency, and enhancing framework performance for large-scale training and inference. \n <br><br>\n To support these efforts, we provide a 100B-tokens subset randomly sampled from the CCI4.0-M2-v1 dataset, along with the open-source baseline model OpenSeek-Small-Baseline-v1. Both the model and dataset serve as strong starting points for participants. Additionally, compute resources are available for selected teams, and top-performing solutions from each track will be integrated into the OpenSeek open-source initiative.\n ",linkText:"Competition Details",link:"https://www.aicompetition-pz.com/topic_detail/25",imageUrl:"/Competition1.png",layout:"image-left"},{title:"Challenge: Enhancing Chinese Performance of Base Models",description:"\n The competition primarily explored new directions for refining and optimizing Chinese pretraining datasets, offering valuable insights for future dataset construction. Several participant solutions contributed to improving the quality of Chinese samples, and their ideas have been partially incorporated into the CCI4.0-M2-v1 dataset to enhance its overall effectiveness.\n ",linkText:"Competition Details",link:"https://www.dcic-china.com/competitions/10166",imageUrl:"/Competition2.jpg",layout:"image-right"}])})},[["render",function(e,r,_,x,T,I){const M=s("a-button"),S=s("a-carousel");return t(),i(l,null,[r[1]||(r[1]=o("h2",{class:"section-title"},"Competitions",-1)),o("section",g,[o("div",f,[a(S,{autoplay:""},{default:n((()=>[(t(!0),i(l,null,p(x.philosophyItems,((e,s)=>(t(),i("div",{key:s,class:"philosophy-carousel-item"},[o("div",{class:c(["philosophy-item-content","image-left"===e.layout?"layout-image-left":"layout-image-right"])},[o("div",u,[o("img",{src:e.imageUrl,alt:"Placeholder Image",class:"item-image"},null,8,y),0==s?(t(),i("h5",v,h(e.title),1)):m("",!0)]),o("div",k,[0!=s?(t(),i("h3",C,h(e.title),1)):m("",!0),o("p",{class:"philosophy-item-description",innerHTML:e.description},null,8,b),o("div",w,[r[0]||(r[0]=o("a",{href:"#",_block:""},null,-1)),a(M,{type:"link",href:e.link,class:"philosophy-item-btn",target:"_blank"},{default:n((()=>[d(h(e.linkText)+" → ",1)])),_:2},1032,["href"])])])],2)])))),128))])),_:1})])])],64)}],["__scopeId","data-v-871a5e11"]]);export{_ as default}; | |