import{S as z6,i as Y6,s as V6,e as a,k as i,w as T,t as l,M as q6,c as r,d as t,m as h,a as o,x as b,h as n,b as s,G as e,g,y,L as K6,q as w,o as A,B as k,v as X6}from"../chunks/vendor-hf-doc-builder.js";import{I as G}from"../chunks/IconCopyLink-hf-doc-builder.js";import{C as Eb}from"../chunks/CodeBlock-hf-doc-builder.js";function Q6(_b){let we,xf,Ae,Pe,sn,Ja,Hc,hn,Jc,Lf,Ql,Wc,Mf,je,Zc,Wa,Uc,Fc,Gf,S,Za,zc,dn,Yc,Vc,qc,Ua,Kc,fn,Xc,Qc,eu,Fa,tu,cn,au,ru,ou,za,lu,un,nu,su,Bf,R,iu,Ya,hu,du,en,fu,cu,Va,uu,gu,Cf,Oe,pu,qa,mu,vu,If,ke,$e,gn,Ka,Eu,pn,_u,Nf,He,Tu,mn,bu,yu,Pf,Je,Xa,Qa,vn,wu,Au,er,En,ku,Du,tr,_n,ar,Su,Tn,rr,jf,We,Ru,bn,xu,Lu,Of,or,$f,De,Ze,yn,lr,Mu,wn,Gu,Hf,tn,Bu,Jf,x,an,An,Cu,Iu,Nu,rn,kn,Pu,ju,Ou,on,Dn,$u,Hu,Ju,ln,Sn,Wu,Zu,Wf,Se,Ue,Rn,nr,Uu,xn,Fu,Zf,Fe,zu,sr,Yu,Vu,Uf,Te,qu,ir,Ku,Xu,hr,Qu,eg,Ff,Re,ze,Ln,dr,tg,Mn,ag,zf,xe,Ye,Gn,fr,rg,Bn,og,Yf,Ve,Cn,B,In,lg,ng,Nn,sg,ig,Pn,hg,dg,jn,fg,cg,p,C,On,cr,ug,gg,$n,Hn,pg,mg,Jn,vg,Eg,Wn,_g,Tg,I,Zn,ur,bg,yg,Un,Fn,wg,Ag,zn,kg,Dg,qe,Sg,gr,Rg,xg,pr,Lg,Mg,N,Yn,mr,Gg,Bg,Vn,qn,Cg,Ig,Kn,Ng,Pg,Ke,jg,vr,Og,$g,Er,Hg,Jg,P,Xn,_r,Wg,Zg,Qn,es,Ug,Fg,ts,zg,Yg,Xe,Vg,Tr,qg,Kg,br,Xg,Qg,j,as,yr,ep,tp,rs,os,ap,rp,ls,op,lp,Qe,np,wr,sp,ip,Ar,hp,dp,O,ns,kr,fp,cp,ss,is,up,gp,hs,pp,mp,ds,vp,Ep,$,fs,Dr,_p,Tp,Sr,cs,bp,yp,us,wp,Ap,gs,kp,Dp,et,Sp,Rr,Rp,xp,xr,Lp,Mp,H,ps,Lr,Gp,Bp,ms,vs,Cp,Ip,Es,Np,Pp,tt,jp,Mr,Op,$p,Gr,Hp,Jp,J,_s,Br,Wp,Zp,Ts,bs,Up,Fp,ys,zp,Yp,at,Vp,Cr,qp,Kp,Ir,Xp,Qp,W,ws,Nr,em,tm,Pr,As,am,rm,ks,om,lm,Ds,nm,sm,rt,im,jr,hm,dm,Or,fm,cm,Z,Ss,$r,um,gm,Rs,xs,pm,mm,Ls,vm,Em,ot,_m,Hr,Tm,bm,Jr,ym,wm,U,Ms,Wr,Am,km,Gs,Bs,Dm,Sm,Cs,Rm,xm,lt,Lm,Zr,Mm,Gm,Ur,Bm,Vf,Le,nt,Is,Fr,Cm,Ns,Im,qf,st,Ps,F,js,Nm,Pm,Os,jm,Om,$s,$m,Hm,Hs,Jm,Wm,v,z,Js,zr,Zm,Um,Ws,Zs,Fm,zm,Us,Ym,Vm,Fs,qm,Km,Y,zs,Yr,Xm,Qm,Ys,Vs,ev,tv,qs,av,rv,it,ov,Vr,lv,nv,qr,sv,iv,V,Ks,Kr,hv,dv,Xs,Qs,fv,cv,ei,uv,gv,ht,pv,Xr,mv,vv,Qr,Ev,_v,q,ti,eo,Tv,bv,ai,ri,yv,wv,oi,Av,kv,li,Dv,Sv,K,ni,to,Rv,xv,si,ii,Lv,Mv,hi,Gv,Bv,di,Cv,Iv,X,fi,ao,Nv,Pv,ci,ui,jv,Ov,gi,$v,Hv,dt,Jv,ro,Wv,Zv,oo,Uv,Fv,Q,pi,lo,zv,Yv,mi,Vv,qv,vi,Kv,Xv,Ei,Qv,e1,ee,_i,no,t1,a1,Ti,r1,o1,bi,l1,n1,yi,s1,Kf,Me,ft,wi,so,i1,Ai,h1,Xf,ct,ki,te,Di,d1,f1,Si,c1,u1,Ri,g1,p1,xi,m1,v1,ae,re,Li,io,E1,_1,Mi,Gi,T1,b1,Bi,y1,w1,ut,A1,ho,k1,D1,fo,S1,R1,oe,Ci,co,x1,L1,Ii,M1,G1,Ni,B1,C1,Pi,I1,N1,le,ji,uo,P1,j1,Oi,$i,O1,$1,Hi,H1,J1,gt,W1,go,Z1,U1,po,F1,z1,ne,Ji,mo,Y1,V1,Wi,q1,K1,Zi,X1,Q1,Ui,eE,Qf,Ge,pt,Fi,vo,tE,zi,aE,ec,mt,Yi,se,Vi,rE,oE,qi,lE,nE,Ki,sE,iE,Xi,hE,dE,Eo,ie,Qi,_o,fE,cE,eh,uE,gE,th,pE,mE,ah,vE,EE,he,rh,To,_E,TE,oh,bE,yE,lh,wE,AE,nh,kE,tc,Be,vt,sh,bo,DE,ih,SE,ac,Et,hh,de,dh,RE,xE,fh,LE,ME,ch,GE,BE,uh,CE,IE,_,fe,gh,yo,NE,PE,ph,mh,jE,OE,vh,$E,HE,Eh,JE,WE,ce,_h,wo,ZE,UE,Th,bh,FE,zE,yh,YE,VE,_t,qE,Ao,KE,XE,ko,QE,e2,ue,wh,Do,t2,a2,Ah,kh,r2,o2,Dh,l2,n2,Tt,s2,So,i2,h2,Ro,d2,f2,ge,Sh,xo,c2,u2,Rh,xh,g2,p2,Lh,m2,v2,Mh,E2,_2,pe,Gh,Lo,T2,b2,Bh,Ch,y2,w2,Ih,A2,k2,Nh,D2,S2,me,Ph,Mo,R2,x2,jh,Oh,L2,M2,$h,G2,B2,bt,C2,Go,I2,N2,Bo,P2,rc,Ce,yt,Hh,Co,j2,Jh,O2,oc,wt,Wh,ve,Zh,$2,H2,Uh,J2,W2,Fh,Z2,U2,zh,F2,z2,Yh,Ee,Vh,Io,Y2,V2,qh,q2,K2,Kh,X2,Q2,Xh,e_,lc,Ie,At,Qh,No,t_,ed,a_,nc,f,kt,td,Po,r_,o_,jo,l_,n_,s_,Dt,ad,Oo,i_,h_,$o,d_,f_,c_,St,rd,Ho,u_,g_,Jo,p_,m_,v_,Rt,od,Wo,E_,__,Zo,T_,b_,y_,xt,ld,Uo,w_,A_,Fo,k_,D_,S_,Lt,nd,zo,R_,x_,Yo,L_,M_,G_,Mt,sd,Vo,B_,C_,qo,I_,N_,P_,Gt,id,Ko,j_,O_,Xo,$_,H_,J_,Bt,hd,Qo,W_,Z_,el,U_,F_,z_,D,dd,tl,Y_,V_,al,q_,K_,rl,X_,Q_,ol,eT,tT,ll,aT,rT,oT,Ct,fd,nl,lT,nT,sl,sT,iT,hT,It,cd,il,dT,fT,hl,cT,uT,gT,L,ud,dl,pT,mT,fl,vT,ET,gd,_T,TT,pd,bT,yT,wT,Nt,md,cl,AT,kT,ul,DT,ST,RT,Pt,vd,gl,xT,LT,pl,MT,GT,BT,be,Ed,ml,CT,IT,vl,NT,PT,El,jT,OT,$T,jt,_d,_l,HT,JT,Tl,WT,ZT,UT,Ot,Td,bl,FT,zT,yl,YT,VT,qT,$t,bd,wl,KT,XT,Al,QT,e3,t3,Ht,yd,kl,a3,r3,Dl,o3,l3,n3,Jt,wd,Sl,s3,i3,Rl,h3,d3,f3,Wt,Ad,xl,c3,u3,Ll,g3,p3,m3,Zt,kd,Ml,v3,E3,Gl,_3,T3,b3,Ut,Dd,Bl,y3,w3,Cl,A3,k3,D3,Ft,Sd,Il,S3,R3,Nl,x3,L3,M3,zt,Rd,Pl,G3,B3,jl,C3,I3,N3,Yt,xd,Ol,P3,j3,$l,O3,$3,H3,Vt,Ld,Hl,J3,W3,Jl,Z3,U3,F3,qt,Md,Wl,z3,Y3,Zl,V3,q3,K3,Kt,Gd,Ul,X3,Q3,Fl,eb,tb,ab,ye,Bd,zl,rb,ob,Yl,lb,nb,Cd,sb,ib,hb,Xt,Id,Vl,db,fb,ql,cb,ub,sc;return Ja=new G({}),Ka=new G({}),ar=new Eb({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMHBpcGVsaW5lJTBBJTBBJTIzJTIwQWxsb2NhdGUlMjBhJTIwcGlwZWxpbmUlMjBmb3IlMjBzZW50aW1lbnQtYW5hbHlzaXMlMEFwaXBlJTIwJTNEJTIwcGlwZWxpbmUoJ3NlbnRpbWVudC1hbmFseXNpcycpJTBBJTBBb3V0JTIwJTNEJTIwcGlwZSgnSSUyMGxvdmUlMjB0cmFuc2Zvcm1lcnMhJyklMEElMjMlMjAlNUIlN0InbGFiZWwnJTNBJTIwJ1BPU0lUSVZFJyUyQyUyMCdzY29yZSclM0ElMjAwLjk5OTgwNjk0MSU3RCU1RA==",highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

<span class="hljs-comment"># Allocate a pipeline for sentiment-analysis</span>
pipe = pipeline(<span class="hljs-string">&#x27;sentiment-analysis&#x27;</span>)

out = pipe(<span class="hljs-string">&#x27;I love transformers!&#x27;</span>)
<span class="hljs-comment"># [{&#x27;label&#x27;: &#x27;POSITIVE&#x27;, &#x27;score&#x27;: 0.999806941}]</span>`}}),rr=new Eb({props:{code:"aW1wb3J0JTIwJTdCJTIwcGlwZWxpbmUlMjAlN0QlMjBmcm9tJTIwJyU0MHhlbm92YSUyRnRyYW5zZm9ybWVycyclM0IlMEElMEElMkYlMkYlMjBBbGxvY2F0ZSUyMGElMjBwaXBlbGluZSUyMGZvciUyMHNlbnRpbWVudC1hbmFseXNpcyUwQWxldCUyMHBpcGUlMjAlM0QlMjBhd2FpdCUyMHBpcGVsaW5lKCdzZW50aW1lbnQtYW5hbHlzaXMnKSUzQiUwQSUwQWxldCUyMG91dCUyMCUzRCUyMGF3YWl0JTIwcGlwZSgnSSUyMGxvdmUlMjB0cmFuc2Zvcm1lcnMhJyklM0IlMEElMkYlMkYlMjAlNUIlN0InbGFiZWwnJTNBJTIwJ1BPU0lUSVZFJyUyQyUyMCdzY29yZSclM0ElMjAwLjk5OTgxNzY4NiU3RCU1RA==",highlighted:`<span class="hljs-keyword">import</span> { pipeline } <span class="hljs-keyword">from</span> <span class="hljs-string">&#x27;@xenova/transformers&#x27;</span>;

<span class="hljs-comment">// Allocate a pipeline for sentiment-analysis</span>
<span class="hljs-keyword">let</span> pipe = <span class="hljs-keyword">await</span> <span class="hljs-title function_">pipeline</span>(<span class="hljs-string">&#x27;sentiment-analysis&#x27;</span>);

<span class="hljs-keyword">let</span> out = <span class="hljs-keyword">await</span> <span class="hljs-title function_">pipe</span>(<span class="hljs-string">&#x27;I love transformers!&#x27;</span>);
<span class="hljs-comment">// [{&#x27;label&#x27;: &#x27;POSITIVE&#x27;, &#x27;score&#x27;: 0.999817686}]</span>`}}),or=new Eb({props:{code:"JTJGJTJGJTIwVXNlJTIwYSUyMGRpZmZlcmVudCUyMG1vZGVsJTIwZm9yJTIwc2VudGltZW50LWFuYWx5c2lzJTBBbGV0JTIwcGlwZSUyMCUzRCUyMGF3YWl0JTIwcGlwZWxpbmUoJ3NlbnRpbWVudC1hbmFseXNpcyclMkMlMjAnbmxwdG93biUyRmJlcnQtYmFzZS1tdWx0aWxpbmd1YWwtdW5jYXNlZC1zZW50aW1lbnQnKSUzQg==",highlighted:`<span class="hljs-comment">// Use a different model for sentiment-analysis</span>
<span class="hljs-keyword">let</span> pipe = <span class="hljs-keyword">await</span> <span class="hljs-title function_">pipeline</span>(<span class="hljs-string">&#x27;sentiment-analysis&#x27;</span>, <span class="hljs-string">&#x27;nlptown/bert-base-multilingual-uncased-sentiment&#x27;</span>);`}}),lr=new G({}),nr=new G({}),dr=new G({}),fr=new G({}),Fr=new G({}),so=new G({}),vo=new G({}),bo=new G({}),Co=new G({}),No=new G({}),{c(){we=a("meta"),xf=i(),Ae=a("h1"),Pe=a("a"),sn=a("span"),T(Ja.$$.fragment),Hc=i(),hn=a("span"),Jc=l("Transformers.js"),Lf=i(),Ql=a("p"),Wc=l("State-of-the-art Machine Learning for the web. Run \u{1F917} Transformers directly in your browser, with no need for a server!"),Mf=i(),je=a("p"),Zc=l("Transformers.js is designed to be functionally equivalent to Hugging Face\u2019s "),Wa=a("a"),Uc=l("transformers"),Fc=l(" python library, meaning you can run the same pretrained models using a very similar API. These models support common tasks in different modalities, such as:"),Gf=i(),S=a("ul"),Za=a("li"),zc=l("\u{1F4DD} "),dn=a("strong"),Yc=l("Natural Language Processing"),Vc=l(": text classification, named entity recognition, question answering, language modeling, summarization, translation, multiple choice, and text generation."),qc=i(),Ua=a("li"),Kc=l("\u{1F5BC}\uFE0F "),fn=a("strong"),Xc=l("Computer Vision"),Qc=l(": image classification, object detection, and segmentation."),eu=i(),Fa=a("li"),tu=l("\u{1F5E3}\uFE0F "),cn=a("strong"),au=l("Audio"),ru=l(": automatic speech recognition and audio classification."),ou=i(),za=a("li"),lu=l("\u{1F419} "),un=a("strong"),nu=l("Multimodal"),su=l(": zero-shot image classification."),Bf=i(),R=a("p"),iu=l("Transformers.js uses "),Ya=a("a"),hu=l("ONNX Runtime"),du=l(" to run models in the browser. The best part about it, is that you can easily "),en=a("a"),fu=l("convert"),cu=l(" your pretrained PyTorch, TensorFlow, or JAX models to ONNX using "),Va=a("a"),uu=l("\u{1F917} Optimum"),gu=l("."),Cf=i(),Oe=a("p"),pu=l("For more information, check out the full "),qa=a("a"),mu=l("documentation"),vu=l("."),If=i(),ke=a("h2"),$e=a("a"),gn=a("span"),T(Ka.$$.fragment),Eu=i(),pn=a("span"),_u=l("Quick tour"),Nf=i(),He=a("p"),Tu=l("It\u2019s super simple to translate from existing code! Just like the python library, we support the "),mn=a("code"),bu=l("pipeline"),yu=l(" API. Pipelines group together a pretrained model with preprocessing of inputs and postprocessing of outputs, making it the easiest way to run models with the library."),Pf=i(),Je=a("table"),Xa=a("tr"),Qa=a("th"),vn=a("b"),wu=l("Python (original)"),Au=i(),er=a("th"),En=a("b"),ku=l("Javascript (ours)"),Du=i(),tr=a("tr"),_n=a("td"),T(ar.$$.fragment),Su=i(),Tn=a("td"),T(rr.$$.fragment),jf=i(),We=a("p"),Ru=l("You can also use a different model by specifying the model id or path as the second argument to the "),bn=a("code"),xu=l("pipeline"),Lu=l(" function. For example:"),Of=i(),T(or.$$.fragment),$f=i(),De=a("h2"),Ze=a("a"),yn=a("span"),T(lr.$$.fragment),Mu=i(),wn=a("span"),Gu=l("Contents"),Hf=i(),tn=a("p"),Bu=l("The documentation is organized into 4 sections:"),Jf=i(),x=a("ol"),an=a("li"),An=a("strong"),Cu=l("GET STARTED"),Iu=l(" provides a quick tour of the library and installation instructions to get up and running."),Nu=i(),rn=a("li"),kn=a("strong"),Pu=l("TUTORIALS"),ju=l(" are a great place to start if you\u2019re a beginner! We also include sample applications for you to play around with!"),Ou=i(),on=a("li"),Dn=a("strong"),$u=l("DEVELOPER GUIDES"),Hu=l(" show you how to use the library to achieve a specific goal."),Ju=i(),ln=a("li"),Sn=a("strong"),Wu=l("API REFERENCE"),Zu=l(" describes all classes and functions, as well as their available parameters and types."),Wf=i(),Se=a("h2"),Ue=a("a"),Rn=a("span"),T(nr.$$.fragment),Uu=i(),xn=a("span"),Fu=l("Supported tasks/models"),Zf=i(),Fe=a("p"),zu=l(`Here is the list of all tasks and architectures currently supported by Transformers.js.
If you don\u2019t see your task/model listed here or it is not yet supported, feel free
to open up a feature request `),sr=a("a"),Yu=l("here"),Vu=l("."),Uf=i(),Te=a("p"),qu=l("To find compatible models on the Hub, select the \u201Ctransformers.js\u201D library tag in the filter menu (or visit "),ir=a("a"),Ku=l("this link"),Xu=l(`).
You can refine your search by selecting the task you\u2019re interested in (e.g., `),hr=a("a"),Qu=l("text-classification"),eg=l(")."),Ff=i(),Re=a("h3"),ze=a("a"),Ln=a("span"),T(dr.$$.fragment),tg=i(),Mn=a("span"),ag=l("Tasks"),zf=i(),xe=a("h4"),Ye=a("a"),Gn=a("span"),T(fr.$$.fragment),rg=i(),Bn=a("span"),og=l("Natural Language Processing"),Yf=i(),Ve=a("table"),Cn=a("thead"),B=a("tr"),In=a("th"),lg=l("Task"),ng=i(),Nn=a("th"),sg=l("ID"),ig=i(),Pn=a("th"),hg=l("Description"),dg=i(),jn=a("th"),fg=l("Supported?"),cg=i(),p=a("tbody"),C=a("tr"),On=a("td"),cr=a("a"),ug=l("Conversational"),gg=i(),$n=a("td"),Hn=a("code"),pg=l("conversational"),mg=i(),Jn=a("td"),vg=l("Generating conversational text that is relevant, coherent and knowledgable given a prompt."),Eg=i(),Wn=a("td"),_g=l("\u274C"),Tg=i(),I=a("tr"),Zn=a("td"),ur=a("a"),bg=l("Fill-Mask"),yg=i(),Un=a("td"),Fn=a("code"),wg=l("fill-mask"),Ag=i(),zn=a("td"),kg=l("Masking some of the words in a sentence and predicting which words should replace those masks."),Dg=i(),qe=a("td"),Sg=l("\u2705 "),gr=a("a"),Rg=l("(docs)"),xg=a("br"),pr=a("a"),Lg=l("(models)"),Mg=i(),N=a("tr"),Yn=a("td"),mr=a("a"),Gg=l("Question Answering"),Bg=i(),Vn=a("td"),qn=a("code"),Cg=l("question-answering"),Ig=i(),Kn=a("td"),Ng=l("Retrieve the answer to a question from a given text."),Pg=i(),Ke=a("td"),jg=l("\u2705 "),vr=a("a"),Og=l("(docs)"),$g=a("br"),Er=a("a"),Hg=l("(models)"),Jg=i(),P=a("tr"),Xn=a("td"),_r=a("a"),Wg=l("Sentence Similarity"),Zg=i(),Qn=a("td"),es=a("code"),Ug=l("sentence-similarity"),Fg=i(),ts=a("td"),zg=l("Determining how similar two texts are."),Yg=i(),Xe=a("td"),Vg=l("\u2705 "),Tr=a("a"),qg=l("(docs)"),Kg=a("br"),br=a("a"),Xg=l("(models)"),Qg=i(),j=a("tr"),as=a("td"),yr=a("a"),ep=l("Summarization"),tp=i(),rs=a("td"),os=a("code"),ap=l("summarization"),rp=i(),ls=a("td"),op=l("Producing a shorter version of a document while preserving its important information."),lp=i(),Qe=a("td"),np=l("\u2705 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