import{S as rt,i as it,s as pt,e as n,k as c,w as f,t as l,M as ct,c as r,d as s,m,a as i,x as h,h as t,b as d,N as mt,G as a,g as p,y as g,q as y,o as M,B as v,v as dt}from"../chunks/vendor-hf-doc-builder.js";import{T as ut}from"../chunks/Tip-hf-doc-builder.js";import{I as la}from"../chunks/IconCopyLink-hf-doc-builder.js";import{C as I}from"../chunks/CodeBlock-hf-doc-builder.js";function ft(ta){let u,z,j,x,G;return{c(){u=n("p"),z=l("Acesse a documenta\xE7\xE3o do "),j=n("code"),x=l("pipeline()"),G=l(" para obter uma lista completa de tarefas poss\xEDveis.")},l($){u=r($,"P",{});var E=i(u);z=t(E,"Acesse a documenta\xE7\xE3o do "),j=r(E,"CODE",{});var V=i(j);x=t(V,"pipeline()"),V.forEach(s),G=t(E," para obter uma lista completa de tarefas poss\xEDveis."),E.forEach(s)},m($,E){p($,u,E),a(u,z),a(u,j),a(j,x),a(u,G)},d($){$&&s(u)}}}function ht(ta){let u,z,j,x,G,$,E,V,Ya,oa,P,Oa,L,La,Qa,na,_,Q,Ka,_e,es,as,ss,ke,ls,ts,K,os,Je,ns,rs,ra,A,ia,C,R,Ze,ee,is,Te,ps,pa,w,cs,Ie,ms,ds,Ge,us,fs,Ce,hs,gs,ca,je,ae,ys,We,Ms,vs,ma,se,da,le,te,js,qe,bs,Us,ua,oe,fa,be,$s,ha,ne,ga,b,xs,Be,ws,Es,ze,_s,ks,Ve,Js,Zs,Pe,Ts,Is,ya,re,Ma,W,S,Ae,ie,Gs,Re,Cs,va,U,Ws,Se,qs,Bs,pe,zs,Vs,Xe,Ps,As,He,Rs,Ss,ja,ce,ba,X,Xs,De,Hs,Ds,Ua,me,$a,H,Ns,Ne,Fs,Ys,xa,de,wa,q,D,Fe,ue,Os,Ye,Ls,Ea,k,Qs,Oe,Ks,el,Le,al,sl,_a,J,ll,fe,tl,ol,Qe,nl,rl,ka,he,Ja,N,il,Ke,pl,cl,Za,ge,Ta,B,F,ea,ye,ml,aa,dl,Ia,Y,ul,sa,fl,hl,Ga,Ue,$e,gl,Ca,Me,Wa;return $=new la({}),A=new ut({props:{$$slots:{default:[ft]},$$scope:{ctx:ta}}}),ee=new la({}),se=new I({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMHBpcGVsaW5lJTBBJTBBZ2VuZXJhdG9yJTIwJTNEJTIwcGlwZWxpbmUodGFzayUzRCUyMnRleHQtZ2VuZXJhdGlvbiUyMik=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>generator = pipeline(task=<span class="hljs-string">&quot;text-generation&quot;</span>)`}}),oe=new I({props:{code:"Z2VuZXJhdG9yKCUyMlRocmVlJTIwUmluZ3MlMjBmb3IlMjB0aGUlMjBFbHZlbi1raW5ncyUyMHVuZGVyJTIwdGhlJTIwc2t5JTJDJTIwU2V2ZW4lMjBmb3IlMjB0aGUlMjBEd2FyZi1sb3JkcyUyMGluJTIwdGhlaXIlMjBoYWxscyUyMG9mJTIwc3RvbmUlMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>generator(<span class="hljs-string">&quot;Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone&quot;</span>)
[{<span class="hljs-string">&#x27;generated_text&#x27;</span>: <span class="hljs-string">&#x27;Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, Seven for the Iron-priests at the door to the east, and thirteen for the Lord Kings at the end of the mountain&#x27;</span>}]`}}),ne=new I({props:{code:"Z2VuZXJhdG9yKCUwQSUyMCUyMCUyMCUyMCU1QiUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMlRocmVlJTIwUmluZ3MlMjBmb3IlMjB0aGUlMjBFbHZlbi1raW5ncyUyMHVuZGVyJTIwdGhlJTIwc2t5JTJDJTIwU2V2ZW4lMjBmb3IlMjB0aGUlMjBEd2FyZi1sb3JkcyUyMGluJTIwdGhlaXIlMjBoYWxscyUyMG9mJTIwc3RvbmUlMjIlMkMlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjJOaW5lJTIwZm9yJTIwTW9ydGFsJTIwTWVuJTJDJTIwZG9vbWVkJTIwdG8lMjBkaWUlMkMlMjBPbmUlMjBmb3IlMjB0aGUlMjBEYXJrJTIwTG9yZCUyMG9uJTIwaGlzJTIwZGFyayUyMHRocm9uZSUyMiUyQyUwQSUyMCUyMCUyMCUyMCU1RCUwQSk=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>generator(
<span class="hljs-meta">... </span>    [
<span class="hljs-meta">... </span>        <span class="hljs-string">&quot;Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone&quot;</span>,
<span class="hljs-meta">... </span>        <span class="hljs-string">&quot;Nine for Mortal Men, doomed to die, One for the Dark Lord on his dark throne&quot;</span>,
<span class="hljs-meta">... </span>    ]
<span class="hljs-meta">... </span>)`}}),re=new I({props:{code:"Z2VuZXJhdG9yKCUwQSUyMCUyMCUyMCUyMCUyMlRocmVlJTIwUmluZ3MlMjBmb3IlMjB0aGUlMjBFbHZlbi1raW5ncyUyMHVuZGVyJTIwdGhlJTIwc2t5JTJDJTIwU2V2ZW4lMjBmb3IlMjB0aGUlMjBEd2FyZi1sb3JkcyUyMGluJTIwdGhlaXIlMjBoYWxscyUyMG9mJTIwc3RvbmUlMjIlMkMlMEElMjAlMjAlMjAlMjBudW1fcmV0dXJuX3NlcXVlbmNlcyUzRDIlMkMlMEEp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>generator(
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone&quot;</span>,
<span class="hljs-meta">... </span>    num_return_sequences=<span class="hljs-number">2</span>,
<span class="hljs-meta">... </span>)`}}),ie=new la({}),ce=new I({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMEF1dG9Ub2tlbml6ZXIlMkMlMjBBdXRvTW9kZWxGb3JDYXVzYWxMTSUwQSUwQXRva2VuaXplciUyMCUzRCUyMEF1dG9Ub2tlbml6ZXIuZnJvbV9wcmV0cmFpbmVkKCUyMmRpc3RpbGdwdDIlMjIpJTBBbW9kZWwlMjAlM0QlMjBBdXRvTW9kZWxGb3JDYXVzYWxMTS5mcm9tX3ByZXRyYWluZWQoJTIyZGlzdGlsZ3B0MiUyMik=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer, AutoModelForCausalLM

<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;distilgpt2&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = AutoModelForCausalLM.from_pretrained(<span class="hljs-string">&quot;distilgpt2&quot;</span>)`}}),me=new I({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMHBpcGVsaW5lJTBBJTBBZ2VuZXJhdG9yJTIwJTNEJTIwcGlwZWxpbmUodGFzayUzRCUyMnRleHQtZ2VuZXJhdGlvbiUyMiUyQyUyMG1vZGVsJTNEbW9kZWwlMkMlMjB0b2tlbml6ZXIlM0R0b2tlbml6ZXIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>generator = pipeline(task=<span class="hljs-string">&quot;text-generation&quot;</span>, model=model, tokenizer=tokenizer)`}}),de=new I({props:{code:"Z2VuZXJhdG9yKCUyMlRocmVlJTIwUmluZ3MlMjBmb3IlMjB0aGUlMjBFbHZlbi1raW5ncyUyMHVuZGVyJTIwdGhlJTIwc2t5JTJDJTIwU2V2ZW4lMjBmb3IlMjB0aGUlMjBEd2FyZi1sb3JkcyUyMGluJTIwdGhlaXIlMjBoYWxscyUyMG9mJTIwc3RvbmUlMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>generator(<span class="hljs-string">&quot;Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone&quot;</span>)
[{<span class="hljs-string">&#x27;generated_text&#x27;</span>: <span class="hljs-string">&#x27;Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, Seven for the Dragon-lords (for them to rule in a world ruled by their rulers, and all who live within the realm&#x27;</span>}]`}}),ue=new la({}),he=new I({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMHBpcGVsaW5lJTBBJTBBYXVkaW9fY2xhc3NpZmllciUyMCUzRCUyMHBpcGVsaW5lKCUwQSUyMCUyMCUyMCUyMHRhc2slM0QlMjJhdWRpby1jbGFzc2lmaWNhdGlvbiUyMiUyQyUyMG1vZGVsJTNEJTIyZWhjYWxhYnJlcyUyRndhdjJ2ZWMyLWxnLXhsc3ItZW4tc3BlZWNoLWVtb3Rpb24tcmVjb2duaXRpb24lMjIlMEEp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>audio_classifier = pipeline(
<span class="hljs-meta">... </span>    task=<span class="hljs-string">&quot;audio-classification&quot;</span>, model=<span class="hljs-string">&quot;ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition&quot;</span>
<span class="hljs-meta">... </span>)`}}),ge=new I({props:{code:"YXVkaW9fY2xhc3NpZmllciglMjJqZmtfbW9vbl9zcGVlY2gud2F2JTIyKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>audio_classifier(<span class="hljs-string">&quot;jfk_moon_speech.wav&quot;</span>)
[{<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;calm&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.13856211304664612</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;disgust&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.13148026168346405</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;happy&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.12635163962841034</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;angry&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.12439591437578201</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;fearful&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.12404385954141617</span>}]`}}),ye=new la({}),Me=new I({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMHBpcGVsaW5lJTBBJTBBdmlzaW9uX2NsYXNzaWZpZXIlMjAlM0QlMjBwaXBlbGluZSh0YXNrJTNEJTIyaW1hZ2UtY2xhc3NpZmljYXRpb24lMjIpJTBBdmlzaW9uX2NsYXNzaWZpZXIoJTBBJTIwJTIwJTIwJTIwaW1hZ2VzJTNEJTIyaHR0cHMlM0ElMkYlMkZodWdnaW5nZmFjZS5jbyUyRmRhdGFzZXRzJTJGaHVnZ2luZ2ZhY2UlMkZkb2N1bWVudGF0aW9uLWltYWdlcyUyRnJlc29sdmUlMkZtYWluJTJGcGlwZWxpbmUtY2F0LWNob25rLmpwZWclMjIlMEEp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>vision_classifier = pipeline(task=<span class="hljs-string">&quot;image-classification&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>vision_classifier(
<span class="hljs-meta">... </span>    images=<span class="hljs-string">&quot;https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg&quot;</span>
<span class="hljs-meta">... </span>)
[{<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;lynx, catamount&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.4403027892112732</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;cougar, puma, catamount, mountain lion, painter, panther, Felis concolor&#x27;</span>,
  <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.03433405980467796</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;snow leopard, ounce, Panthera uncia&#x27;</span>,
  <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.032148055732250214</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;Egyptian cat&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.02353910356760025</span>},
 {<span class="hljs-string">&#x27;label&#x27;</span>: <span class="hljs-string">&#x27;tiger cat&#x27;</span>, <span class="hljs-string">&#x27;score&#x27;</span>: <span class="hljs-number">0.023034192621707916</span>}]`}}),{c(){u=n("meta"),z=c(),j=n("h1"),x=n("a"),G=n("span"),f($.$$.fragment),E=c(),V=n("span"),Ya=l("Pipelines para infer\xEAncia"),oa=c(),P=n("p"),Oa=l("Um [pipeline] simplifica o uso dos modelos no "),L=n("a"),La=l("Model Hub"),Qa=l(` para a infer\xEAncia de uma diversidade de tarefas,
como a gera\xE7\xE3o de texto, a segmenta\xE7\xE3o de imagens e a classifica\xE7\xE3o de \xE1udio.
Inclusive, se n\xE3o tem experi\xEAncia com alguma modalidade espec\xEDfica ou n\xE3o compreende o c\xF3digo que forma os modelos,
pode usar eles mesmo assim com o [pipeline]! Este tutorial te ensinar\xE1 a:`),na=c(),_=n("ul"),Q=n("li"),Ka=l("Utilizar um "),_e=n("code"),es=l("pipeline()"),as=l(" para infer\xEAncia."),ss=c(),ke=n("li"),ls=l("Utilizar um tokenizador ou model espec\xEDfico."),ts=c(),K=n("li"),os=l("Utilizar um "),Je=n("code"),ns=l("pipeline()"),rs=l(" para tarefas de \xE1udio e vis\xE3o computacional."),ra=c(),f(A.$$.fragment),ia=c(),C=n("h2"),R=n("a"),Ze=n("span"),f(ee.$$.fragment),is=c(),Te=n("span"),ps=l("Uso do pipeline"),pa=c(),w=n("p"),cs=l("Mesmo que cada tarefa tenha um "),Ie=n("code"),ms=l("pipeline()"),ds=l(" associado, \xE9 mais simples usar a abstra\xE7\xE3o geral do "),Ge=n("code"),us=l("pipeline()"),fs=l(` que
cont\xE9m todos os pipelines das tarefas mais espec\xEDficas.
O `),Ce=n("code"),hs=l("pipeline()"),gs=l(` carrega automaticamenta um modelo predeterminado e um tokenizador com capacidade de infer\xEAncia para sua
tarefa.`),ca=c(),je=n("ol"),ae=n("li"),ys=l("Comece carregando um "),We=n("code"),Ms=l("pipeline()"),vs=l(" e especifique uma tarefa de infer\xEAncia:"),ma=c(),f(se.$$.fragment),da=c(),le=n("ol"),te=n("li"),js=l("Passe seu dado de entrada, no caso um texto, ao "),qe=n("code"),bs=l("pipeline()"),Us=l(":"),ua=c(),f(oe.$$.fragment),fa=c(),be=n("p"),$s=l("Se tiver mais de uma entrada, passe-a como uma lista:"),ha=c(),f(ne.$$.fragment),ga=c(),b=n("p"),xs=l("Qualquer par\xE2metro adicional para a sua tarefa tamb\xE9m pode ser inclu\xEDdo no "),Be=n("code"),ws=l("pipeline()"),Es=l(". A tarefa "),ze=n("code"),_s=l("text-generation"),ks=l(` tem um m\xE9todo
`),Ve=n("code"),Js=l("generate()"),Zs=l(` com v\xE1rios par\xE2metros para controlar a sa\xEDda.
Por exemplo, se quiser gerar mais de uma sa\xEDda, defina-a no par\xE2metro `),Pe=n("code"),Ts=l("num_return_sequences"),Is=l(":"),ya=c(),f(re.$$.fragment),Ma=c(),W=n("h3"),S=n("a"),Ae=n("span"),f(ie.$$.fragment),Gs=c(),Re=n("span"),Cs=l("Selecionando um modelo e um tokenizador"),va=c(),U=n("p"),Ws=l("O "),Se=n("code"),qs=l("pipeline()"),Bs=l(" aceita qualquer modelo do "),pe=n("a"),zs=l("Model Hub"),Vs=l(`. H\xE1 r\xF3tulos adicionais no Model Hub
que te permitem filtrar pelo modelo que gostaria de usar para sua tarefa. Uma vez que tiver escolhido o modelo apropriado,
carregue-o com as classes `),Xe=n("code"),Ps=l("AutoModelFor"),As=l(" e [`AutoTokenizer\u2019] correspondentes. Por exemplo, carregue a classe "),He=n("code"),Rs=l("AutoModelForCausalLM"),Ss=l(`
para uma tarefa de modelagem de linguagem causal:`),ja=c(),f(ce.$$.fragment),ba=c(),X=n("p"),Xs=l("Crie uma "),De=n("code"),Hs=l("pipeline()"),Ds=l(" para a sua tarefa e especif\xEDque o modelo e o tokenizador que foram carregados:"),Ua=c(),f(me.$$.fragment),$a=c(),H=n("p"),Ns=l("Passe seu texto de entrada ao "),Ne=n("code"),Fs=l("pipeline()"),Ys=l(" para gerar algum texto:"),xa=c(),f(de.$$.fragment),wa=c(),q=n("h2"),D=n("a"),Fe=n("span"),f(ue.$$.fragment),Os=c(),Ye=n("span"),Ls=l("Pipeline de audio"),Ea=c(),k=n("p"),Qs=l("A flexibilidade do "),Oe=n("code"),Ks=l("pipeline()"),el=l(` significa que tamb\xE9m pode-se extender \xE0s tarefas de \xE1udio.
La flexibilidad de `),Le=n("code"),al=l("pipeline()"),sl=l(" significa que tambi\xE9n se puede extender a tareas de audio."),_a=c(),J=n("p"),ll=l(`Por exemplo, classifiquemos a emo\xE7\xE3o de um breve fragmento do famoso discurso de John F. Kennedy /home/rzimmerdev/dev/transformers/docs/source/pt/pipeline_tutorial.md
Encontre um modelo de `),fe=n("a"),tl=l("audio classification"),ol=l(` para
reconhecimento de emo\xE7\xF5es no Model Hub e carregue-o usando o `),Qe=n("code"),nl=l("pipeline()"),rl=l(":"),ka=c(),f(he.$$.fragment),Ja=c(),N=n("p"),il=l("Passe o arquivo de \xE1udio ao "),Ke=n("code"),pl=l("pipeline()"),cl=l(":"),Za=c(),f(ge.$$.fragment),Ta=c(),B=n("h2"),F=n("a"),ea=n("span"),f(ye.$$.fragment),ml=c(),aa=n("span"),dl=l("Pipeline de vis\xE3o computacional"),Ia=c(),Y=n("p"),ul=l("Finalmente, utilizar um "),sa=n("code"),fl=l("pipeline()"),hl=l(` para tarefas de vis\xE3o \xE9 praticamente a mesma coisa.
Especifique a sua tarefa de vis\xE3o e passe a sua imagem ao classificador.
A imagem pode ser um link ou uma rota local \xE0 imagem. Por exemplo, que esp\xE9cie de gato est\xE1 presente na imagem?`),Ga=c(),Ue=n("p"),$e=n("img"),Ca=c(),f(Me.$$.fragment),this.h()},l(e){const o=ct('[data-svelte="svelte-1phssyn"]',document.head);u=r(o,"META",{name:!0,content:!0}),o.forEach(s),z=m(e),j=r(e,"H1",{class:!0});var ve=i(j);x=r(ve,"A",{id:!0,class:!0,href:!0});var yl=i(x);G=r(yl,"SPAN",{});var Ml=i(G);h($.$$.fragment,Ml),Ml.forEach(s),yl.forEach(s),E=m(ve),V=r(ve,"SPAN",{});var vl=i(V);Ya=t(vl,"Pipelines para infer\xEAncia"),vl.forEach(s),ve.forEach(s),oa=m(e),P=r(e,"P",{});var qa=i(P);Oa=t(qa,"Um [pipeline] simplifica o uso dos modelos no "),L=r(qa,"A",{href:!0,rel:!0});var jl=i(L);La=t(jl,"Model Hub"),jl.forEach(s),Qa=t(qa,` para a infer\xEAncia de uma diversidade de tarefas,
como a gera\xE7\xE3o de texto, a segmenta\xE7\xE3o de imagens e a classifica\xE7\xE3o de \xE1udio.
Inclusive, se n\xE3o tem experi\xEAncia com alguma modalidade espec\xEDfica ou n\xE3o compreende o c\xF3digo que forma os modelos,
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O `),Ce=r(O,"CODE",{});var Jl=i(Ce);hs=t(Jl,"pipeline()"),Jl.forEach(s),gs=t(O,` carrega automaticamenta um modelo predeterminado e um tokenizador com capacidade de infer\xEAncia para sua
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que te permitem filtrar pelo modelo que gostaria de usar para sua tarefa. Uma vez que tiver escolhido o modelo apropriado,
carregue-o com as classes `),Xe=r(T,"CODE",{});var Xl=i(Xe);Ps=t(Xl,"AutoModelFor"),Xl.forEach(s),As=t(T," e [`AutoTokenizer\u2019] correspondentes. Por exemplo, carregue a classe "),He=r(T,"CODE",{});var Hl=i(He);Rs=t(Hl,"AutoModelForCausalLM"),Hl.forEach(s),Ss=t(T,`
para uma tarefa de modelagem de linguagem causal:`),T.forEach(s),ja=m(e),h(ce.$$.fragment,e),ba=m(e),X=r(e,"P",{});var Sa=i(X);Xs=t(Sa,"Crie uma "),De=r(Sa,"CODE",{});var Dl=i(De);Hs=t(Dl,"pipeline()"),Dl.forEach(s),Ds=t(Sa," para a sua tarefa e especif\xEDque o modelo e o tokenizador que foram carregados:"),Sa.forEach(s),Ua=m(e),h(me.$$.fragment,e),$a=m(e),H=r(e,"P",{});var Xa=i(H);Ns=t(Xa,"Passe seu texto de entrada ao "),Ne=r(Xa,"CODE",{});var Nl=i(Ne);Fs=t(Nl,"pipeline()"),Nl.forEach(s),Ys=t(Xa," para gerar algum texto:"),Xa.forEach(s),xa=m(e),h(de.$$.fragment,e),wa=m(e),q=r(e,"H2",{class:!0});var Ha=i(q);D=r(Ha,"A",{id:!0,class:!0,href:!0});var Fl=i(D);Fe=r(Fl,"SPAN",{});var Yl=i(Fe);h(ue.$$.fragment,Yl),Yl.forEach(s),Fl.forEach(s),Os=m(Ha),Ye=r(Ha,"SPAN",{});var Ol=i(Ye);Ls=t(Ol,"Pipeline de audio"),Ol.forEach(s),Ha.forEach(s),Ea=m(e),k=r(e,"P",{});var we=i(k);Qs=t(we,"A flexibilidade do "),Oe=r(we,"CODE",{});var Ll=i(Oe);Ks=t(Ll,"pipeline()"),Ll.forEach(s),el=t(we,` significa que tamb\xE9m pode-se extender \xE0s tarefas de \xE1udio.
La flexibilidad de `),Le=r(we,"CODE",{});var Ql=i(Le);al=t(Ql,"pipeline()"),Ql.forEach(s),sl=t(we," significa que tambi\xE9n se puede extender a tareas de audio."),we.forEach(s),_a=m(e),J=r(e,"P",{});var Ee=i(J);ll=t(Ee,`Por exemplo, classifiquemos a emo\xE7\xE3o de um breve fragmento do famoso discurso de John F. Kennedy /home/rzimmerdev/dev/transformers/docs/source/pt/pipeline_tutorial.md
Encontre um modelo de `),fe=r(Ee,"A",{href:!0,rel:!0});var Kl=i(fe);tl=t(Kl,"audio classification"),Kl.forEach(s),ol=t(Ee,` para
reconhecimento de emo\xE7\xF5es no Model Hub e carregue-o usando o `),Qe=r(Ee,"CODE",{});var et=i(Qe);nl=t(et,"pipeline()"),et.forEach(s),rl=t(Ee,":"),Ee.forEach(s),ka=m(e),h(he.$$.fragment,e),Ja=m(e),N=r(e,"P",{});var Da=i(N);il=t(Da,"Passe o arquivo de \xE1udio ao "),Ke=r(Da,"CODE",{});var at=i(Ke);pl=t(at,"pipeline()"),at.forEach(s),cl=t(Da,":"),Da.forEach(s),Za=m(e),h(ge.$$.fragment,e),Ta=m(e),B=r(e,"H2",{class:!0});var Na=i(B);F=r(Na,"A",{id:!0,class:!0,href:!0});var st=i(F);ea=r(st,"SPAN",{});var lt=i(ea);h(ye.$$.fragment,lt),lt.forEach(s),st.forEach(s),ml=m(Na),aa=r(Na,"SPAN",{});var tt=i(aa);dl=t(tt,"Pipeline de vis\xE3o computacional"),tt.forEach(s),Na.forEach(s),Ia=m(e),Y=r(e,"P",{});var Fa=i(Y);ul=t(Fa,"Finalmente, utilizar um "),sa=r(Fa,"CODE",{});var ot=i(sa);fl=t(ot,"pipeline()"),ot.forEach(s),hl=t(Fa,` para tarefas de vis\xE3o \xE9 praticamente a mesma coisa.
Especifique a sua tarefa de vis\xE3o e passe a sua imagem ao classificador.
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