import{S as Oi,i as Ri,s as Gi,e as o,k as n,w as ro,t as h,M as Ii,c as r,d as a,m as i,a as l,x as lo,h as c,b as e,$ as E,G as t,g,y as no,L as Pi,q as io,o as so,B as ho,v as $i}from"../chunks/vendor-hf-doc-builder.js";import{I as co}from"../chunks/IconCopyLink-hf-doc-builder.js";function Ui(Al){let T,qa,y,B,fa,lt,fo,da,uo,Ma,Ft,go,Fa,k,X,ua,nt,mo,ga,po,La,C,ma,D,Lt,bo,_o,Bt,vo,wo,pa,Eo,f,x,Xt,it,To,yo,Ct,ko,Do,Wt,st,Yt,Sl,xo,A,jt,ht,Ao,So,Kt,Ho,No,ba,Oo,S,Qt,ct,Ro,Go,Jt,Io,Po,_a,$o,H,Vt,ft,Uo,zo,Zt,qo,Mo,te,dt,ee,Hl,Fo,N,ae,ut,Lo,Bo,oe,Xo,Co,va,Wo,O,re,gt,Yo,jo,le,Ko,Qo,wa,Jo,R,ne,mt,Vo,Zo,ie,tr,er,Ea,ar,G,se,pt,or,rr,he,lr,nr,Ta,ir,I,ce,bt,sr,hr,fe,cr,fr,ya,dr,P,de,_t,ur,gr,ue,mr,pr,ka,br,$,ge,vt,_r,vr,me,wr,Er,Da,Tr,U,pe,wt,yr,kr,be,Dr,xr,_e,Et,ve,Nl,Ar,z,we,Tt,Sr,Hr,Ee,Nr,Or,xa,Rr,q,Te,yt,Gr,Ir,ye,Pr,$r,Aa,Ba,M,W,Sa,kt,Ur,Ha,zr,Xa,Y,Na,m,ke,qr,Mr,De,Fr,Lr,Oa,Br,Ra,Xr,Ga,p,xe,Dt,Cr,Wr,j,Yr,xt,jr,Kr,Qr,Ae,At,Se,Ol,Jr,He,St,Ne,Rl,Ca,F,K,Ia,Ht,Vr,Pa,Zr,Wa,Q,$a,b,Oe,tl,el,Re,al,ol,Ua,rl,za,ll,L,_,Ge,Nt,nl,il,J,sl,Ot,hl,cl,fl,Ie,Rt,Pe,Gl,dl,$e,Gt,Ue,Il,ul,v,ze,It,gl,ml,V,pl,Pt,bl,_l,vl,qe,$t,Me,Pl,wl,Fe,Ut,Le,$l,El,w,Be,zt,Tl,yl,Xe,kl,Dl,Ce,qt,We,Ul,xl,Ye,Mt,je,zl,Ya;return lt=new co({}),nt=new co({}),kt=new co({}),Ht=new co({}),{c(){T=o("meta"),qa=n(),y=o("h1"),B=o("a"),fa=o("span"),ro(lt.$$.fragment),fo=n(),da=o("span"),uo=h("\u{1F917} Optimum notebooks"),Ma=n(),Ft=o("p"),go=h("You can find here a list of the notebooks associated with each accelerator in \u{1F917} Optimum."),Fa=n(),k=o("h2"),X=o("a"),ua=o("span"),ro(nt.$$.fragment),mo=n(),ga=o("span"),po=h("Optimum Graphcore examples"),La=n(),C=o("table"),ma=o("thead"),D=o("tr"),Lt=o("th"),bo=h("Notebook"),_o=n(),Bt=o("th"),vo=h("Description"),wo=n(),pa=o("th"),Eo=n(),f=o("tbody"),x=o("tr"),Xt=o("td"),it=o("a"),To=h("Introduction to Optimum Graphcore"),yo=n(),Ct=o("td"),ko=h("Introduce Optimum-Graphcore with a BERT fine-tuning example."),Do=n(),Wt=o("td"),st=o("a"),Yt=o("img"),xo=n(),A=o("tr"),jt=o("td"),ht=o("a"),Ao=h("Train an external model"),So=n(),Kt=o("td"),Ho=h("Show how to train an external model that is not supported by Optimum or Transformers."),No=n(),ba=o("td"),Oo=n(),S=o("tr"),Qt=o("td"),ct=o("a"),Ro=h("Train your language model"),Go=n(),Jt=o("td"),Io=h("Show how to train a model for causal or masked language modelling from scratch."),Po=n(),_a=o("td"),$o=n(),H=o("tr"),Vt=o("td"),ft=o("a"),Uo=h("How to fine-tune a model on text classification"),zo=n(),Zt=o("td"),qo=h("Show how to preprocess the data and fine-tune a pretrained model on any GLUE task."),Mo=n(),te=o("td"),dt=o("a"),ee=o("img"),Fo=n(),N=o("tr"),ae=o("td"),ut=o("a"),Lo=h("How to fine-tune a model on language modeling"),Bo=n(),oe=o("td"),Xo=h("Show how to preprocess the data and fine-tune a pretrained model on a causal or masked LM task."),Co=n(),va=o("td"),Wo=n(),O=o("tr"),re=o("td"),gt=o("a"),Yo=h("How to fine-tune a model on token classification"),jo=n(),le=o("td"),Ko=h("Show how to preprocess the data and fine-tune a pretrained model on a token classification task (NER, PoS)."),Qo=n(),wa=o("td"),Jo=n(),R=o("tr"),ne=o("td"),mt=o("a"),Vo=h("How to fine-tune a model on question answering"),Zo=n(),ie=o("td"),tr=h("Show how to preprocess the data and fine-tune a pretrained model on SQUAD."),er=n(),Ea=o("td"),ar=n(),G=o("tr"),se=o("td"),pt=o("a"),or=h("How to fine-tune a model on multiple choice"),rr=n(),he=o("td"),lr=h("Show how to preprocess the data and fine-tune a pretrained model on SWAG."),nr=n(),Ta=o("td"),ir=n(),I=o("tr"),ce=o("td"),bt=o("a"),sr=h("How to fine-tune a model on translation"),hr=n(),fe=o("td"),cr=h("Show how to preprocess the data and fine-tune a pretrained model on WMT."),fr=n(),ya=o("td"),dr=n(),P=o("tr"),de=o("td"),_t=o("a"),ur=h("How to fine-tune a model on summarization"),gr=n(),ue=o("td"),mr=h("Show how to preprocess the data and fine-tune a pretrained model on XSUM."),pr=n(),ka=o("td"),br=n(),$=o("tr"),ge=o("td"),vt=o("a"),_r=h("How to fine-tune a model on audio classification"),vr=n(),me=o("td"),wr=h("Show how to preprocess the data and fine-tune a pretrained Speech model on Keyword Spotting"),Er=n(),Da=o("td"),Tr=n(),U=o("tr"),pe=o("td"),wt=o("a"),yr=h("How to fine-tune a model on image classfication"),kr=n(),be=o("td"),Dr=h("Show how to preprocess the data and fine-tune a pretrained model on image classification."),xr=n(),_e=o("td"),Et=o("a"),ve=o("img"),Ar=n(),z=o("tr"),we=o("td"),Tt=o("a"),Sr=h("wav2vec 2.0 Fine-Tuning on IPU"),Hr=n(),Ee=o("td"),Nr=h("How to fine-tune a pre-trained wav2vec 2.0 model with PyTorch on the Graphcore IPU-POD16 system."),Or=n(),xa=o("td"),Rr=n(),q=o("tr"),Te=o("td"),yt=o("a"),Gr=h("wav2vec 2.0 Inference on IPU"),Ir=n(),ye=o("td"),Pr=h("How to run inference on the wav2vec 2.0 model with PyTorch on the Graphcore IPU-POD16 system."),$r=n(),Aa=o("td"),Ba=n(),M=o("h2"),W=o("a"),Sa=o("span"),ro(kt.$$.fragment),Ur=n(),Ha=o("span"),zr=h("Optimum Intel examples"),Xa=n(),Y=o("table"),Na=o("thead"),m=o("tr"),ke=o("th"),qr=h("Notebook"),Mr=n(),De=o("th"),Fr=h("Description"),Lr=n(),Oa=o("th"),Br=n(),Ra=o("th"),Xr=n(),Ga=o("tbody"),p=o("tr"),xe=o("td"),Dt=o("a"),Cr=h("How to quantize a model with Intel Neural Compressor for text classification"),Wr=n(),j=o("td"),Yr=h("Show how to apply static, dynamic and aware training quantization on a model using "),xt=o("a"),jr=h("Intel Neural Compressor (INC)"),Kr=h(" for any GLUE task."),Qr=n(),Ae=o("td"),At=o("a"),Se=o("img"),Jr=n(),He=o("td"),St=o("a"),Ne=o("img"),Ca=n(),F=o("h2"),K=o("a"),Ia=o("span"),ro(Ht.$$.fragment),Vr=n(),Pa=o("span"),Zr=h("ONNX Runtime examples"),Wa=n(),Q=o("table"),$a=o("thead"),b=o("tr"),Oe=o("th"),tl=h("Notebook"),el=n(),Re=o("th"),al=h("Description"),ol=n(),Ua=o("th"),rl=n(),za=o("th"),ll=n(),L=o("tbody"),_=o("tr"),Ge=o("td"),Nt=o("a"),nl=h("How to quantize a model with ONNX Runtime for text classification"),il=n(),J=o("td"),sl=h("Show how to apply static and dynamic quantization on a model using "),Ot=o("a"),hl=h("ONNX Runtime"),cl=h(" for any GLUE task."),fl=n(),Ie=o("td"),Rt=o("a"),Pe=o("img"),dl=n(),$e=o("td"),Gt=o("a"),Ue=o("img"),ul=n(),v=o("tr"),ze=o("td"),It=o("a"),gl=h("How to fine-tune a model for text classification with ONNX Runtime"),ml=n(),V=o("td"),pl=h("Show how to DistilBERT model on GLUE tasks using "),Pt=o("a"),bl=h("ONNX Runtime"),_l=h("."),vl=n(),qe=o("td"),$t=o("a"),Me=o("img"),wl=n(),Fe=o("td"),Ut=o("a"),Le=o("img"),El=n(),w=o("tr"),Be=o("td"),zt=o("a"),Tl=h("How to fine-tune a model for summarization with ONNX Runtime"),yl=n(),Xe=o("td"),kl=h("Show how to fine-tune a T5 model on the BBC news corpus."),Dl=n(),Ce=o("td"),qt=o("a"),We=o("img"),xl=n(),Ye=o("td"),Mt=o("a"),je=o("img"),this.h()},l(s){const u=Ii('[data-svelte="svelte-1phssyn"]',document.head);T=r(u,"META",{name:!0,content:!0}),u.forEach(a),qa=i(s),y=r(s,"H1",{class:!0});var ja=l(y);B=r(ja,"A",{id:!0,class:!0,href:!0});var ql=l(B);fa=r(ql,"SPAN",{});var Ml=l(fa);lo(lt.$$.fragment,Ml),Ml.forEach(a),ql.forEach(a),fo=i(ja),da=r(ja,"SPAN",{});var Fl=l(da);uo=c(Fl,"\u{1F917} Optimum notebooks"),Fl.forEach(a),ja.forEach(a),Ma=i(s),Ft=r(s,"P",{});var Ll=l(Ft);go=c(Ll,"You can find here a list of the notebooks associated with each accelerator in \u{1F917} Optimum."),Ll.forEach(a),Fa=i(s),k=r(s,"H2",{class:!0});var Ka=l(k);X=r(Ka,"A",{id:!0,class:!0,href:!0});var Bl=l(X);ua=r(Bl,"SPAN",{});var Xl=l(ua);lo(nt.$$.fragment,Xl),Xl.forEach(a),Bl.forEach(a),mo=i(Ka),ga=r(Ka,"SPAN",{});var Cl=l(ga);po=c(Cl,"Optimum Graphcore examples"),Cl.forEach(a),Ka.forEach(a),La=i(s),C=r(s,"TABLE",{});var Qa=l(C);ma=r(Qa,"THEAD",{});var Wl=l(ma);D=r(Wl,"TR",{});var Ke=l(D);Lt=r(Ke,"TH",{align:!0});var Yl=l(Lt);bo=c(Yl,"Notebook"),Yl.forEach(a),_o=i(Ke),Bt=r(Ke,"TH",{align:!0});var jl=l(Bt);vo=c(jl,"Description"),jl.forEach(a),wo=i(Ke),pa=r(Ke,"TH",{align:!0}),l(pa).forEach(a),Ke.forEach(a),Wl.forEach(a),Eo=i(Qa),f=r(Qa,"TBODY",{});var d=l(f);x=r(d,"TR",{});var Qe=l(x);Xt=r(Qe,"TD",{align:!0});var Kl=l(Xt);it=r(Kl,"A",{href:!0,rel:!0});var Ql=l(it);To=c(Ql,"Introduction to Optimum Graphcore"),Ql.forEach(a),Kl.forEach(a),yo=i(Qe),Ct=r(Qe,"TD",{align:!0});var Jl=l(Ct);ko=c(Jl,"Introduce Optimum-Graphcore with a BERT fine-tuning example."),Jl.forEach(a),Do=i(Qe),Wt=r(Qe,"TD",{align:!0});var Vl=l(Wt);st=r(Vl,"A",{href:!0,rel:!0});var Zl=l(st);Yt=r(Zl,"IMG",{src:!0,alt:!0}),Zl.forEach(a),Vl.forEach(a),Qe.forEach(a),xo=i(d),A=r(d,"TR",{});var Je=l(A);jt=r(Je,"TD",{align:!0});var tn=l(jt);ht=r(tn,"A",{href:!0,rel:!0});var en=l(ht);Ao=c(en,"Train an external model"),en.forEach(a),tn.forEach(a),So=i(Je),Kt=r(Je,"TD",{align:!0});var an=l(Kt);Ho=c(an,"Show how to train an external model that is not supported by Optimum or Transformers."),an.forEach(a),No=i(Je),ba=r(Je,"TD",{align:!0}),l(ba).forEach(a),Je.forEach(a),Oo=i(d),S=r(d,"TR",{});var Ve=l(S);Qt=r(Ve,"TD",{align:!0});var on=l(Qt);ct=r(on,"A",{href:!0,rel:!0});var rn=l(ct);Ro=c(rn,"Train your language model"),rn.forEach(a),on.forEach(a),Go=i(Ve),Jt=r(Ve,"TD",{align:!0});var ln=l(Jt);Io=c(ln,"Show how to train a model for causal or masked language modelling from scratch."),ln.forEach(a),Po=i(Ve),_a=r(Ve,"TD",{align:!0}),l(_a).forEach(a),Ve.forEach(a),$o=i(d),H=r(d,"TR",{});var Ze=l(H);Vt=r(Ze,"TD",{align:!0});var nn=l(Vt);ft=r(nn,"A",{href:!0,rel:!0});var sn=l(ft);Uo=c(sn,"How to fine-tune a model on text classification"),sn.forEach(a),nn.forEach(a),zo=i(Ze),Zt=r(Ze,"TD",{align:!0});var hn=l(Zt);qo=c(hn,"Show how to preprocess the data and fine-tune a pretrained model on any GLUE task."),hn.forEach(a),Mo=i(Ze),te=r(Ze,"TD",{align:!0});var cn=l(te);dt=r(cn,"A",{href:!0,rel:!0});var fn=l(dt);ee=r(fn,"IMG",{src:!0,alt:!0}),fn.forEach(a),cn.forEach(a),Ze.forEach(a),Fo=i(d),N=r(d,"TR",{});var ta=l(N);ae=r(ta,"TD",{align:!0});var dn=l(ae);ut=r(dn,"A",{href:!0,rel:!0});var un=l(ut);Lo=c(un,"How to fine-tune a model on language modeling"),un.forEach(a),dn.forEach(a),Bo=i(ta),oe=r(ta,"TD",{align:!0});var gn=l(oe);Xo=c(gn,"Show how to preprocess the data and fine-tune a pretrained model on a causal or masked LM task."),gn.forEach(a),Co=i(ta),va=r(ta,"TD",{align:!0}),l(va).forEach(a),ta.forEach(a),Wo=i(d),O=r(d,"TR",{});var ea=l(O);re=r(ea,"TD",{align:!0});var mn=l(re);gt=r(mn,"A",{href:!0,rel:!0});var pn=l(gt);Yo=c(pn,"How to fine-tune a model on token classification"),pn.forEach(a),mn.forEach(a),jo=i(ea),le=r(ea,"TD",{align:!0});var bn=l(le);Ko=c(bn,"Show how to preprocess the data and fine-tune a pretrained model on a token classification task (NER, PoS)."),bn.forEach(a),Qo=i(ea),wa=r(ea,"TD",{align:!0}),l(wa).forEach(a),ea.forEach(a),Jo=i(d),R=r(d,"TR",{});var aa=l(R);ne=r(aa,"TD",{align:!0});var _n=l(ne);mt=r(_n,"A",{href:!0,rel:!0});var vn=l(mt);Vo=c(vn,"How to fine-tune a model on question answering"),vn.forEach(a),_n.forEach(a),Zo=i(aa),ie=r(aa,"TD",{align:!0});var wn=l(ie);tr=c(wn,"Show how to preprocess the data and fine-tune a pretrained model on SQUAD."),wn.forEach(a),er=i(aa),Ea=r(aa,"TD",{align:!0}),l(Ea).forEach(a),aa.forEach(a),ar=i(d),G=r(d,"TR",{});var oa=l(G);se=r(oa,"TD",{align:!0});var En=l(se);pt=r(En,"A",{href:!0,rel:!0});var Tn=l(pt);or=c(Tn,"How to fine-tune a model on multiple choice"),Tn.forEach(a),En.forEach(a),rr=i(oa),he=r(oa,"TD",{align:!0});var yn=l(he);lr=c(yn,"Show how to preprocess the data and fine-tune a pretrained model on SWAG."),yn.forEach(a),nr=i(oa),Ta=r(oa,"TD",{align:!0}),l(Ta).forEach(a),oa.forEach(a),ir=i(d),I=r(d,"TR",{});var ra=l(I);ce=r(ra,"TD",{align:!0});var kn=l(ce);bt=r(kn,"A",{href:!0,rel:!0});var Dn=l(bt);sr=c(Dn,"How to fine-tune a model on translation"),Dn.forEach(a),kn.forEach(a),hr=i(ra),fe=r(ra,"TD",{align:!0});var xn=l(fe);cr=c(xn,"Show how to preprocess the data and fine-tune a pretrained model on WMT."),xn.forEach(a),fr=i(ra),ya=r(ra,"TD",{align:!0}),l(ya).forEach(a),ra.forEach(a),dr=i(d),P=r(d,"TR",{});var la=l(P);de=r(la,"TD",{align:!0});var An=l(de);_t=r(An,"A",{href:!0,rel:!0});var Sn=l(_t);ur=c(Sn,"How to fine-tune a model on summarization"),Sn.forEach(a),An.forEach(a),gr=i(la),ue=r(la,"TD",{align:!0});var Hn=l(ue);mr=c(Hn,"Show how to preprocess the data and fine-tune a pretrained model on XSUM."),Hn.forEach(a),pr=i(la),ka=r(la,"TD",{align:!0}),l(ka).forEach(a),la.forEach(a),br=i(d),$=r(d,"TR",{});var na=l($);ge=r(na,"TD",{align:!0});var Nn=l(ge);vt=r(Nn,"A",{href:!0,rel:!0});var On=l(vt);_r=c(On,"How to fine-tune a model on audio classification"),On.forEach(a),Nn.forEach(a),vr=i(na),me=r(na,"TD",{align:!0});var Rn=l(me);wr=c(Rn,"Show how to preprocess the data and fine-tune a pretrained Speech model on Keyword Spotting"),Rn.forEach(a),Er=i(na),Da=r(na,"TD",{align:!0}),l(Da).forEach(a),na.forEach(a),Tr=i(d),U=r(d,"TR",{});var ia=l(U);pe=r(ia,"TD",{align:!0});var Gn=l(pe);wt=r(Gn,"A",{href:!0,rel:!0});var In=l(wt);yr=c(In,"How to fine-tune a model on image classfication"),In.forEach(a),Gn.forEach(a),kr=i(ia),be=r(ia,"TD",{align:!0});var Pn=l(be);Dr=c(Pn,"Show how to preprocess the data and fine-tune a pretrained model on image classification."),Pn.forEach(a),xr=i(ia),_e=r(ia,"TD",{align:!0});var $n=l(_e);Et=r($n,"A",{href:!0,rel:!0});var Un=l(Et);ve=r(Un,"IMG",{src:!0,alt:!0}),Un.forEach(a),$n.forEach(a),ia.forEach(a),Ar=i(d),z=r(d,"TR",{});var sa=l(z);we=r(sa,"TD",{align:!0});var zn=l(we);Tt=r(zn,"A",{href:!0,rel:!0});var qn=l(Tt);Sr=c(qn,"wav2vec 2.0 Fine-Tuning on IPU"),qn.forEach(a),zn.forEach(a),Hr=i(sa),Ee=r(sa,"TD",{align:!0});var Mn=l(Ee);Nr=c(Mn,"How to fine-tune a pre-trained wav2vec 2.0 model with PyTorch on the Graphcore IPU-POD16 system."),Mn.forEach(a),Or=i(sa),xa=r(sa,"TD",{align:!0}),l(xa).forEach(a),sa.forEach(a),Rr=i(d),q=r(d,"TR",{});var ha=l(q);Te=r(ha,"TD",{align:!0});var Fn=l(Te);yt=r(Fn,"A",{href:!0,rel:!0});var Ln=l(yt);Gr=c(Ln,"wav2vec 2.0 Inference on IPU"),Ln.forEach(a),Fn.forEach(a),Ir=i(ha),ye=r(ha,"TD",{align:!0});var Bn=l(ye);Pr=c(Bn,"How to run inference on the wav2vec 2.0 model with PyTorch on the Graphcore IPU-POD16 system."),Bn.forEach(a),$r=i(ha),Aa=r(ha,"TD",{align:!0}),l(Aa).forEach(a),ha.forEach(a),d.forEach(a),Qa.forEach(a),Ba=i(s),M=r(s,"H2",{class:!0});var Ja=l(M);W=r(Ja,"A",{id:!0,class:!0,href:!0});var Xn=l(W);Sa=r(Xn,"SPAN",{});var Cn=l(Sa);lo(kt.$$.fragment,Cn),Cn.forEach(a),Xn.forEach(a),Ur=i(Ja),Ha=r(Ja,"SPAN",{});var Wn=l(Ha);zr=c(Wn,"Optimum Intel examples"),Wn.forEach(a),Ja.forEach(a),Xa=i(s),Y=r(s,"TABLE",{});var Va=l(Y);Na=r(Va,"THEAD",{});var Yn=l(Na);m=r(Yn,"TR",{});var Z=l(m);ke=r(Z,"TH",{align:!0});var jn=l(ke);qr=c(jn,"Notebook"),jn.forEach(a),Mr=i(Z),De=r(Z,"TH",{align:!0});var Kn=l(De);Fr=c(Kn,"Description"),Kn.forEach(a),Lr=i(Z),Oa=r(Z,"TH",{align:!0}),l(Oa).forEach(a),Br=i(Z),Ra=r(Z,"TH",{align:!0}),l(Ra).forEach(a),Z.forEach(a),Yn.forEach(a),Xr=i(Va),Ga=r(Va,"TBODY",{});var Qn=l(Ga);p=r(Qn,"TR",{});var tt=l(p);xe=r(tt,"TD",{align:!0});var Jn=l(xe);Dt=r(Jn,"A",{href:!0,rel:!0});var Vn=l(Dt);Cr=c(Vn,"How to quantize a model with Intel Neural Compressor for text classification"),Vn.forEach(a),Jn.forEach(a),Wr=i(tt),j=r(tt,"TD",{align:!0});var Za=l(j);Yr=c(Za,"Show how to apply static, dynamic and aware training quantization on a model using "),xt=r(Za,"A",{href:!0,rel:!0});var Zn=l(xt);jr=c(Zn,"Intel Neural Compressor (INC)"),Zn.forEach(a),Kr=c(Za," for any GLUE task."),Za.forEach(a),Qr=i(tt),Ae=r(tt,"TD",{align:!0});var ti=l(Ae);At=r(ti,"A",{href:!0,rel:!0});var ei=l(At);Se=r(ei,"IMG",{src:!0,alt:!0}),ei.forEach(a),ti.forEach(a),Jr=i(tt),He=r(tt,"TD",{align:!0});var ai=l(He);St=r(ai,"A",{href:!0,rel:!0});var oi=l(St);Ne=r(oi,"IMG",{src:!0,alt:!0}),oi.forEach(a),ai.forEach(a),tt.forEach(a),Qn.forEach(a),Va.forEach(a),Ca=i(s),F=r(s,"H2",{class:!0});var to=l(F);K=r(to,"A",{id:!0,class:!0,href:!0});var ri=l(K);Ia=r(ri,"SPAN",{});var li=l(Ia);lo(Ht.$$.fragment,li),li.forEach(a),ri.forEach(a),Vr=i(to),Pa=r(to,"SPAN",{});var ni=l(Pa);Zr=c(ni,"ONNX Runtime examples"),ni.forEach(a),to.forEach(a),Wa=i(s),Q=r(s,"TABLE",{});var eo=l(Q);$a=r(eo,"THEAD",{});var ii=l($a);b=r(ii,"TR",{});var et=l(b);Oe=r(et,"TH",{align:!0});var si=l(Oe);tl=c(si,"Notebook"),si.forEach(a),el=i(et),Re=r(et,"TH",{align:!0});var hi=l(Re);al=c(hi,"Description"),hi.forEach(a),ol=i(et),Ua=r(et,"TH",{align:!0}),l(Ua).forEach(a),rl=i(et),za=r(et,"TH",{align:!0}),l(za).forEach(a),et.forEach(a),ii.forEach(a),ll=i(eo),L=r(eo,"TBODY",{});var ca=l(L);_=r(ca,"TR",{});var at=l(_);Ge=r(at,"TD",{align:!0});var ci=l(Ge);Nt=r(ci,"A",{href:!0,rel:!0});var fi=l(Nt);nl=c(fi,"How to quantize a model with ONNX Runtime for text classification"),fi.forEach(a),ci.forEach(a),il=i(at),J=r(at,"TD",{align:!0});var ao=l(J);sl=c(ao,"Show how to apply static and dynamic quantization on a model using "),Ot=r(ao,"A",{href:!0,rel:!0});var di=l(Ot);hl=c(di,"ONNX Runtime"),di.forEach(a),cl=c(ao," for any GLUE task."),ao.forEach(a),fl=i(at),Ie=r(at,"TD",{align:!0});var ui=l(Ie);Rt=r(ui,"A",{href:!0,rel:!0});var gi=l(Rt);Pe=r(gi,"IMG",{src:!0,alt:!0}),gi.forEach(a),ui.forEach(a),dl=i(at),$e=r(at,"TD",{align:!0});var mi=l($e);Gt=r(mi,"A",{href:!0,rel:!0});var pi=l(Gt);Ue=r(pi,"IMG",{src:!0,alt:!0}),pi.forEach(a),mi.forEach(a),at.forEach(a),ul=i(ca),v=r(ca,"TR",{});var ot=l(v);ze=r(ot,"TD",{align:!0});var bi=l(ze);It=r(bi,"A",{href:!0,rel:!0});var _i=l(It);gl=c(_i,"How to fine-tune a model for text classification with ONNX Runtime"),_i.forEach(a),bi.forEach(a),ml=i(ot),V=r(ot,"TD",{align:!0});var oo=l(V);pl=c(oo,"Show how to DistilBERT model on GLUE tasks using "),Pt=r(oo,"A",{href:!0,rel:!0});var vi=l(Pt);bl=c(vi,"ONNX Runtime"),vi.forEach(a),_l=c(oo,"."),oo.forEach(a),vl=i(ot),qe=r(ot,"TD",{align:!0});var wi=l(qe);$t=r(wi,"A",{href:!0,rel:!0});var Ei=l($t);Me=r(Ei,"IMG",{src:!0,alt:!0}),Ei.forEach(a),wi.forEach(a),wl=i(ot),Fe=r(ot,"TD",{align:!0});var Ti=l(Fe);Ut=r(Ti,"A",{href:!0,rel:!0});var yi=l(Ut);Le=r(yi,"IMG",{src:!0,alt:!0}),yi.forEach(a),Ti.forEach(a),ot.forEach(a),El=i(ca),w=r(ca,"TR",{});var rt=l(w);Be=r(rt,"TD",{align:!0});var ki=l(Be);zt=r(ki,"A",{href:!0,rel:!0});var Di=l(zt);Tl=c(Di,"How to fine-tune a model for summarization with ONNX Runtime"),Di.forEach(a),ki.forEach(a),yl=i(rt),Xe=r(rt,"TD",{align:!0});var xi=l(Xe);kl=c(xi,"Show how to fine-tune a T5 model on the BBC news corpus."),xi.forEach(a),Dl=i(rt),Ce=r(rt,"TD",{align:!0});var Ai=l(Ce);qt=r(Ai,"A",{href:!0,rel:!0});var Si=l(qt);We=r(Si,"IMG",{src:!0,alt:!0}),Si.forEach(a),Ai.forEach(a),xl=i(rt),Ye=r(rt,"TD",{align:!0});var Hi=l(Ye);Mt=r(Hi,"A",{href:!0,rel:!0});var Ni=l(Mt);je=r(Ni,"IMG",{src:!0,alt:!0}),Ni.forEach(a),Hi.forEach(a),rt.forEach(a),ca.forEach(a),eo.forEach(a),this.h()},h(){e(T,"name","hf:doc:metadata"),e(T,"content",JSON.stringify(zi)),e(B,"id","optimum-notebooks"),e(B,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),e(B,"href","#optimum-notebooks"),e(y,"class","relative group"),e(X,"id","optimum-graphcore-examples"),e(X,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),e(X,"href","#optimum-graphcore-examples"),e(k,"class","relative group"),e(Lt,"align","left"),e(Bt,"align","left"),e(pa,"align","left"),e(it,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/introduction_to_optimum_graphcore.ipynb"),e(it,"rel","nofollow"),e(Xt,"align","left"),e(Ct,"align","left"),E(Yt.src,Sl="https://assets.paperspace.io/img/gradient-badge.svg")||e(Yt,"src",Sl),e(Yt,"alt","Gradient"),e(st,"href","https://console.paperspace.com/github/gradient-ai/Graphcore-HuggingFace?machine=Free-IPU-POD16&container=graphcore%2Fpytorch-jupyter%3A2.6.0-ubuntu-20.04-20220804&file=%2Fnotebook-tutorials%2Fintroduction_to_optimum_graphcore.ipynb"),e(st,"rel","nofollow"),e(Wt,"align","left"),e(ht,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/external_model.ipynb"),e(ht,"rel","nofollow"),e(jt,"align","left"),e(Kt,"align","left"),e(ba,"align","left"),e(ct,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/language_modelling_from_scratch.ipynb"),e(ct,"rel","nofollow"),e(Qt,"align","left"),e(Jt,"align","left"),e(_a,"align","left"),e(ft,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/text_classification.ipynb"),e(ft,"rel","nofollow"),e(Vt,"align","left"),e(Zt,"align","left"),E(ee.src,Hl="https://assets.paperspace.io/img/gradient-badge.svg")||e(ee,"src",Hl),e(ee,"alt","Gradient"),e(dt,"href","https://console.paperspace.com/github/gradient-ai/Graphcore-HuggingFace?machine=Free-IPU-POD16&container=graphcore%2Fpytorch-jupyter%3A2.6.0-ubuntu-20.04-20220804&file=%2Fnotebook-tutorials%2Ftext_classification.ipynb"),e(dt,"rel","nofollow"),e(te,"align","left"),e(ut,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/language_modeling.ipynb"),e(ut,"rel","nofollow"),e(ae,"align","left"),e(oe,"align","left"),e(va,"align","left"),e(gt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/token_classification.ipynb"),e(gt,"rel","nofollow"),e(re,"align","left"),e(le,"align","left"),e(wa,"align","left"),e(mt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/question_answering.ipynb"),e(mt,"rel","nofollow"),e(ne,"align","left"),e(ie,"align","left"),e(Ea,"align","left"),e(pt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/multiple_choice.ipynb"),e(pt,"rel","nofollow"),e(se,"align","left"),e(he,"align","left"),e(Ta,"align","left"),e(bt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/translation.ipynb"),e(bt,"rel","nofollow"),e(ce,"align","left"),e(fe,"align","left"),e(ya,"align","left"),e(_t,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/summarization.ipynb"),e(_t,"rel","nofollow"),e(de,"align","left"),e(ue,"align","left"),e(ka,"align","left"),e(vt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/audio_classification.ipynb"),e(vt,"rel","nofollow"),e(ge,"align","left"),e(me,"align","left"),e(Da,"align","left"),e(wt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/image_classification.ipynb"),e(wt,"rel","nofollow"),e(pe,"align","left"),e(be,"align","left"),E(ve.src,Nl="https://assets.paperspace.io/img/gradient-badge.svg")||e(ve,"src",Nl),e(ve,"alt","Gradient"),e(Et,"href","https://console.paperspace.com/github/gradient-ai/Graphcore-HuggingFace?machine=Free-IPU-POD16&container=graphcore%2Fpytorch-jupyter%3A2.6.0-ubuntu-20.04-20220804&file=%2Fget-started%2Fwalkthrough.ipynb"),e(Et,"rel","nofollow"),e(_e,"align","left"),e(Tt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/wav2vec2/wav2vec2-fine-tuning-checkpoint.ipynb"),e(Tt,"rel","nofollow"),e(we,"align","left"),e(Ee,"align","left"),e(xa,"align","left"),e(yt,"href","https://github.com/huggingface/optimum-graphcore/blob/main/notebooks/wav2vec2/wav2vec2-inference-checkpoint.ipynb"),e(yt,"rel","nofollow"),e(Te,"align","left"),e(ye,"align","left"),e(Aa,"align","left"),e(W,"id","optimum-intel-examples"),e(W,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),e(W,"href","#optimum-intel-examples"),e(M,"class","relative group"),e(ke,"align","left"),e(De,"align","left"),e(Oa,"align","left"),e(Ra,"align","right"),e(Dt,"href","https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb"),e(Dt,"rel","nofollow"),e(xe,"align","left"),e(xt,"href","https://github.com/intel/neural-compressor"),e(xt,"rel","nofollow"),e(j,"align","left"),E(Se.src,Ol="https://colab.research.google.com/assets/colab-badge.svg")||e(Se,"src",Ol),e(Se,"alt","Open in Colab"),e(At,"href","https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb"),e(At,"rel","nofollow"),e(Ae,"align","left"),E(Ne.src,Rl="https://studiolab.sagemaker.aws/studiolab.svg")||e(Ne,"src",Rl),e(Ne,"alt","Open in AWS Studio"),e(St,"href","https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb"),e(St,"rel","nofollow"),e(He,"align","right"),e(K,"id","onnx-runtime-examples"),e(K,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),e(K,"href","#onnx-runtime-examples"),e(F,"class","relative group"),e(Oe,"align","left"),e(Re,"align","left"),e(Ua,"align","left"),e(za,"align","right"),e(Nt,"href","https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb"),e(Nt,"rel","nofollow"),e(Ge,"align","left"),e(Ot,"href","https://github.com/microsoft/onnxruntime"),e(Ot,"rel","nofollow"),e(J,"align","left"),E(Pe.src,Gl="https://colab.research.google.com/assets/colab-badge.svg")||e(Pe,"src",Gl),e(Pe,"alt","Open in Colab"),e(Rt,"href","https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb"),e(Rt,"rel","nofollow"),e(Ie,"align","left"),E(Ue.src,Il="https://studiolab.sagemaker.aws/studiolab.svg")||e(Ue,"src",Il),e(Ue,"alt","Open in AWS Studio"),e(Gt,"href","https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb"),e(Gt,"rel","nofollow"),e($e,"align","right"),e(It,"href","https://github.com/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb"),e(It,"rel","nofollow"),e(ze,"align","left"),e(Pt,"href","https://github.com/microsoft/onnxruntime"),e(Pt,"rel","nofollow"),e(V,"align","left"),E(Me.src,Pl="https://colab.research.google.com/assets/colab-badge.svg")||e(Me,"src",Pl),e(Me,"alt","Open in Colab"),e($t,"href","https://colab.research.google.com/github.com/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb"),e($t,"rel","nofollow"),e(qe,"align","left"),E(Le.src,$l="https://studiolab.sagemaker.aws/studiolab.svg")||e(Le,"src",$l),e(Le,"alt","Open in AWS Studio"),e(Ut,"href","https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb"),e(Ut,"rel","nofollow"),e(Fe,"align","right"),e(zt,"href","https://github.com/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb"),e(zt,"rel","nofollow"),e(Be,"align","left"),e(Xe,"align","left"),E(We.src,Ul="https://colab.research.google.com/assets/colab-badge.svg")||e(We,"src",Ul),e(We,"alt","Open in Colab"),e(qt,"href","https://colab.research.google.com/github.com/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb"),e(qt,"rel","nofollow"),e(Ce,"align","left"),E(je.src,zl="https://studiolab.sagemaker.aws/studiolab.svg")||e(je,"src",zl),e(je,"alt","Open in AWS Studio"),e(Mt,"href","https://studiolab.sagemaker.aws/import/github.com/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb"),e(Mt,"rel","nofollow"),e(Ye,"align","right")},m(s,u){t(document.head,T),g(s,qa,u),g(s,y,u),t(y,B),t(B,fa),no(lt,fa,null),t(y,fo),t(y,da),t(da,uo),g(s,Ma,u),g(s,Ft,u),t(Ft,go),g(s,Fa,u),g(s,k,u),t(k,X),t(X,ua),no(nt,ua,null),t(k,mo),t(k,ga),t(ga,po),g(s,La,u),g(s,C,u),t(C,ma),t(ma,D),t(D,Lt),t(Lt,bo),t(D,_o),t(D,Bt),t(Bt,vo),t(D,wo),t(D,pa),t(C,Eo),t(C,f),t(f,x),t(x,Xt),t(Xt,it),t(it,To),t(x,yo),t(x,Ct),t(Ct,ko),t(x,Do),t(x,Wt),t(Wt,st),t(st,Yt),t(f,xo),t(f,A),t(A,jt),t(jt,ht),t(ht,Ao),t(A,So),t(A,Kt),t(Kt,Ho),t(A,No),t(A,ba),t(f,Oo),t(f,S),t(S,Qt),t(Qt,ct),t(ct,Ro),t(S,Go),t(S,Jt),t(Jt,Io),t(S,Po),t(S,_a),t(f,$o),t(f,H),t(H,Vt),t(Vt,ft),t(ft,Uo),t(H,zo),t(H,Zt),t(Zt,qo),t(H,Mo),t(H,te),t(te,dt),t(dt,ee),t(f,Fo),t(f,N),t(N,ae),t(ae,ut),t(ut,Lo),t(N,Bo),t(N,oe),t(oe,Xo),t(N,Co),t(N,va),t(f,Wo),t(f,O),t(O,re),t(re,gt),t(gt,Yo),t(O,jo),t(O,le),t(le,Ko),t(O,Qo),t(O,wa),t(f,Jo),t(f,R),t(R,ne),t(ne,mt),t(mt,Vo),t(R,Zo),t(R,ie),t(ie,tr),t(R,er),t(R,Ea),t(f,ar),t(f,G),t(G,se),t(se,pt),t(pt,or),t(G,rr),t(G,he),t(he,lr),t(G,nr),t(G,Ta),t(f,ir),t(f,I),t(I,ce),t(ce,bt),t(bt,sr),t(I,hr),t(I,fe),t(fe,cr),t(I,fr),t(I,ya),t(f,dr),t(f,P),t(P,de),t(de,_t),t(_t,ur),t(P,gr),t(P,ue),t(ue,mr),t(P,pr),t(P,ka),t(f,br),t(f,$),t($,ge),t(ge,vt),t(vt,_r),t($,vr),t($,me),t(me,wr),t($,Er),t($,Da),t(f,Tr),t(f,U),t(U,pe),t(pe,wt),t(wt,yr),t(U,kr),t(U,be),t(be,Dr),t(U,xr),t(U,_e),t(_e,Et),t(Et,ve),t(f,Ar),t(f,z),t(z,we),t(we,Tt),t(Tt,Sr),t(z,Hr),t(z,Ee),t(Ee,Nr),t(z,Or),t(z,xa),t(f,Rr),t(f,q),t(q,Te),t(Te,yt),t(yt,Gr),t(q,Ir),t(q,ye),t(ye,Pr),t(q,$r),t(q,Aa),g(s,Ba,u),g(s,M,u),t(M,W),t(W,Sa),no(kt,Sa,null),t(M,Ur),t(M,Ha),t(Ha,zr),g(s,Xa,u),g(s,Y,u),t(Y,Na),t(Na,m),t(m,ke),t(ke,qr),t(m,Mr),t(m,De),t(De,Fr),t(m,Lr),t(m,Oa),t(m,Br),t(m,Ra),t(Y,Xr),t(Y,Ga),t(Ga,p),t(p,xe),t(xe,Dt),t(Dt,Cr),t(p,Wr),t(p,j),t(j,Yr),t(j,xt),t(xt,jr),t(j,Kr),t(p,Qr),t(p,Ae),t(Ae,At),t(At,Se),t(p,Jr),t(p,He),t(He,St),t(St,Ne),g(s,Ca,u),g(s,F,u),t(F,K),t(K,Ia),no(Ht,Ia,null),t(F,Vr),t(F,Pa),t(Pa,Zr),g(s,Wa,u),g(s,Q,u),t(Q,$a),t($a,b),t(b,Oe),t(Oe,tl),t(b,el),t(b,Re),t(Re,al),t(b,ol),t(b,Ua),t(b,rl),t(b,za),t(Q,ll),t(Q,L),t(L,_),t(_,Ge),t(Ge,Nt),t(Nt,nl),t(_,il),t(_,J),t(J,sl),t(J,Ot),t(Ot,hl),t(J,cl),t(_,fl),t(_,Ie),t(Ie,Rt),t(Rt,Pe),t(_,dl),t(_,$e),t($e,Gt),t(Gt,Ue),t(L,ul),t(L,v),t(v,ze),t(ze,It),t(It,gl),t(v,ml),t(v,V),t(V,pl),t(V,Pt),t(Pt,bl),t(V,_l),t(v,vl),t(v,qe),t(qe,$t),t($t,Me),t(v,wl),t(v,Fe),t(Fe,Ut),t(Ut,Le),t(L,El),t(L,w),t(w,Be),t(Be,zt),t(zt,Tl),t(w,yl),t(w,Xe),t(Xe,kl),t(w,Dl),t(w,Ce),t(Ce,qt),t(qt,We),t(w,xl),t(w,Ye),t(Ye,Mt),t(Mt,je),Ya=!0},p:Pi,i(s){Ya||(io(lt.$$.fragment,s),io(nt.$$.fragment,s),io(kt.$$.fragment,s),io(Ht.$$.fragment,s),Ya=!0)},o(s){so(lt.$$.fragment,s),so(nt.$$.fragment,s),so(kt.$$.fragment,s),so(Ht.$$.fragment,s),Ya=!1},d(s){a(T),s&&a(qa),s&&a(y),ho(lt),s&&a(Ma),s&&a(Ft),s&&a(Fa),s&&a(k),ho(nt),s&&a(La),s&&a(C),s&&a(Ba),s&&a(M),ho(kt),s&&a(Xa),s&&a(Y),s&&a(Ca),s&&a(F),ho(Ht),s&&a(Wa),s&&a(Q)}}}const zi={local:"optimum-notebooks",sections:[{local:"optimum-graphcore-examples",title:"Optimum Graphcore examples"},{local:"optimum-intel-examples",title:"Optimum Intel examples"},{local:"onnx-runtime-examples",title:"ONNX Runtime examples"}],title:"\u{1F917} Optimum notebooks"};function qi(Al){return $i(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class Li extends Oi{constructor(T){super();Ri(this,T,qi,Ui,Gi,{})}}export{Li as default,zi as metadata};
