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"/>`,x,c,y,p,Y="Falcon3 represents a natural evolution from previous releases, emphasizing expanding the models’ science, math, and code capabilities. This iteration includes five base models: Falcon3-1B-Base, Falcon3-3B-Base, Falcon3-Mamba-7B-Base, Falcon3-7B-Base, and Falcon3-10B-Base. In developing these models, we incorporated several key innovations aimed at improving the models’ performances while reducing training costs:",C,m,I=`One pre-training: We conducted a single large-scale pretraining run on the 7B model, using 2048 H100 GPU chips, leveraging 14 trillion tokens featuring web, code, STEM, and curated high-quality and multilingual data.
Depth up-scaling for improved reasoning: Building on recent studies on the effects of model depth, we upscaled the 7B model to a 10B parameters model by duplicating the redundant layers and continuing pre-training with 2TT of high-quality data. This yielded Falcon3-10B-Base which achieves state-of-the-art zero-shot and few-shot performance for models under 13B parameters.
Knowledge distillation for better tiny models: To provide compact and efficient alternatives, we developed Falcon3-1B-Base and Falcon3-3B-Base by leveraging pruning and knowledge distillation techniques, using less than 100GT of curated high-quality data, thereby redefining pre-training efficiency.`,O,d,G,f,W='<li><a href="https://huggingface.co/blog/falcon3" rel="nofollow">Blog post</a></li> <li><a href="https://huggingface.co/collections/tiiuae/falcon3-67605ae03578be86e4e87026" rel="nofollow">Models on Huggingface</a></li>',P,u,J,A,E;return r=new q({props:{title:"Falcon3",local:"falcon3",headingTag:"h1"}}),c=new q({props:{title:"Overview",local:"overview",headingTag:"h2"}}),d=new q({props:{title:"Resources",local:"resources",headingTag:"h2"}}),u=new $({props:{source:"https://github.com/huggingface/transformers/blob/main/docs/source/en/model_doc/falcon3.md"}}),{c(){i=g("meta"),b=l(),v=g("p"),w=l(),L(r.$$.fragment),T=l(),o=g("div"),o.innerHTML=k,x=l(),L(c.$$.fragment),y=l(),p=g("p"),p.textContent=Y,C=l(),m=g("p"),m.textContent=I,O=l(),L(d.$$.fragment),G=l(),f=g("ul"),f.innerHTML=W,P=l(),L(u.$$.fragment),J=l(),A=g("p"),this.h()},l(e){const t=X("svelte-u9bgzb",document.head);i=h(t,"META",{name:!0,content:!0}),t.forEach(a),b=s(e),v=h(e,"P",{}),z(v).forEach(a),w=s(e),B(r.$$.fragment,e),T=s(e),o=h(e,"DIV",{class:!0,"data-svelte-h":!0}),N(o)!=="svelte-1l5icot"&&(o.innerHTML=k),x=s(e),B(c.$$.fragment,e),y=s(e),p=h(e,"P",{"data-svelte-h":!0}),N(p)!=="svelte-324e7g"&&(p.textContent=Y),C=s(e),m=h(e,"P",{"data-svelte-h":!0}),N(m)!=="svelte-1p3hmsh"&&(m.textContent=I),O=s(e),B(d.$$.fragment,e),G=s(e),f=h(e,"UL",{"data-svelte-h":!0}),N(f)!=="svelte-1kksbbi"&&(f.innerHTML=W),P=s(e),B(u.$$.fragment,e),J=s(e),A=h(e,"P",{}),z(A).forEach(a),this.h()},h(){Z(i,"name","hf:doc:metadata"),Z(i,"content",ee),Z(o,"class","flex flex-wrap space-x-1")},m(e,t){j(document.head,i),n(e,b,t),n(e,v,t),n(e,w,t),S(r,e,t),n(e,T,t),n(e,o,t),n(e,x,t),S(c,e,t),n(e,y,t),n(e,p,t),n(e,C,t),n(e,m,t),n(e,O,t),S(d,e,t),n(e,G,t),n(e,f,t),n(e,P,t),S(u,e,t),n(e,J,t),n(e,A,t),E=!0},p:H,i(e){E||(K(r.$$.fragment,e),K(c.$$.fragment,e),K(d.$$.fragment,e),K(u.$$.fragment,e),E=!0)},o(e){M(r.$$.fragment,e),M(c.$$.fragment,e),M(d.$$.fragment,e),M(u.$$.fragment,e),E=!1},d(e){e&&(a(b),a(v),a(w),a(T),a(o),a(x),a(y),a(p),a(C),a(m),a(O),a(G),a(f),a(P),a(J),a(A)),a(i),U(r,e),U(c,e),U(d,e),U(u,e)}}}const ee='{"title":"Falcon3","local":"falcon3","sections":[{"title":"Overview","local":"overview","sections":[],"depth":2},{"title":"Resources","local":"resources","sections":[],"depth":2}],"depth":1}';function te(Q){return R(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class se extends V{constructor(i){super(),D(this,i,te,_,F,{})}}export{se as component};
