import{S as li,i as ei,s as ti,e as a,k as p,w as u,t as r,M as ai,c as s,d as t,m as f,a as o,x as h,h as n,b as c,G as e,g as m,y as d,L as si,q as b,o as M,B as E,v as oi}from"../chunks/vendor-hf-doc-builder.js";import{I as rl}from"../chunks/IconCopyLink-hf-doc-builder.js";import{C as w}from"../chunks/CodeBlock-hf-doc-builder.js";import{D as ri}from"../chunks/DocNotebookDropdown-hf-doc-builder.js";function ni(wr){let $,ut,j,D,me,nl,Ia,pe,Za,ht,il,dt,Q,Ca,fe,Ra,Xa,bt,ml,pl,xa,Va,Mt,I,W,ce,fl,Ga,ue,Da,Et,Zl,Qa,gt,Z,B,he,cl,Wa,de,Ba,vt,Cl,La,Jt,g,Rl,be,Oa,Aa,Na,Xl,Me,Fa,za,qa,xl,Ee,Sa,Pa,Ya,Vl,ge,Ha,Ka,ls,Gl,ve,es,ts,as,Dl,Je,ss,os,rs,Ql,ye,ns,is,yt,y,ms,Ue,ps,fs,_e,cs,us,Te,hs,ds,Ut,L,bs,we,Ms,Es,_t,ul,Tt,O,gs,ke,vs,Js,wt,hl,kt,Wl,ys,$t,dl,jt,U,Us,$e,_s,Ts,je,ws,ks,Ie,$s,js,It,bl,Zt,A,Is,Ze,Zs,Cs,Ct,Ml,Rt,C,El,Rs,Xs,Ce,xs,Vs,Xt,R,N,Re,gl,Gs,Xe,Ds,xt,Bl,Qs,Vt,F,Ll,xe,Ws,Bs,Ls,Ol,Ve,Os,As,Gt,Al,Ns,Dt,X,z,Ge,vl,Fs,De,zs,Qt,Nl,qs,Wt,q,Fl,Qe,Ss,Ps,Ys,zl,We,Hs,Ks,Bt,ql,lo,Lt,x,S,Be,Jl,eo,Le,to,Ot,Sl,ao,At,P,Pl,Oe,so,oo,ro,Yl,Ae,no,io,Nt,Hl,mo,Ft,V,Y,Ne,yl,po,Fe,fo,zt,Kl,co,qt,H,le,ze,uo,ho,bo,ee,qe,Mo,Eo,St,K,go,Se,vo,Jo,Pt,Ul,Yt,te,yo,Ht,_l,Kt,_,Uo,Pe,_o,To,Ye,wo,ko,He,$o,jo,la,Tl,ea,G,ll,Ke,wl,Io,lt,Zo,ta,ae,Co,aa,v,se,et,Ro,Xo,xo,oe,tt,Vo,Go,Do,re,at,Qo,Wo,Bo,ne,st,Lo,Oo,Ao,ot,rt,No,sa,el,Fo,nt,zo,qo,oa,kl,ra,ie,So,na,$l,ia,T,Po,it,Yo,Ho,mt,Ko,lr,pt,er,tr,ma,jl,pa,Il,ft,ar,sr,fa;return nl=new rl({}),il=new ri({props:{classNames:"absolute z-10 right-0 top-0",options:[{label:"Mixed",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/ko/multilingual.ipynb"},{label:"PyTorch",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/ko/pytorch/multilingual.ipynb"},{label:"TensorFlow",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/ko/tensorflow/multilingual.ipynb"},{label:"Mixed",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/ko/multilingual.ipynb"},{label:"PyTorch",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/ko/pytorch/multilingual.ipynb"},{label:"TensorFlow",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/ko/tensorflow/multilingual.ipynb"}]}}),fl=new rl({}),cl=new rl({}),ul=new w({props:{code:"aW1wb3J0JTIwdG9yY2glMEFmcm9tJTIwdHJhbnNmb3JtZXJzJTIwaW1wb3J0JTIwWExNVG9rZW5pemVyJTJDJTIwWExNV2l0aExNSGVhZE1vZGVsJTBBJTBBdG9rZW5pemVyJTIwJTNEJTIwWExNVG9rZW5pemVyLmZyb21fcHJldHJhaW5lZCglMjJ4bG0tY2xtLWVuZnItMTAyNCUyMiklMEFtb2RlbCUyMCUzRCUyMFhMTVdpdGhMTUhlYWRNb2RlbC5mcm9tX3ByZXRyYWluZWQoJTIyeGxtLWNsbS1lbmZyLTEwMjQlMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> torch
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> XLMTokenizer, XLMWithLMHeadModel

<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = XLMTokenizer.from_pretrained(<span class="hljs-string">&quot;xlm-clm-enfr-1024&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = XLMWithLMHeadModel.from_pretrained(<span class="hljs-string">&quot;xlm-clm-enfr-1024&quot;</span>)`}}),hl=new w({props:{code:"cHJpbnQodG9rZW5pemVyLmxhbmcyaWQp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(tokenizer.lang2id)
{<span class="hljs-string">&#x27;en&#x27;</span>: <span class="hljs-number">0</span>, <span class="hljs-string">&#x27;fr&#x27;</span>: <span class="hljs-number">1</span>}`}}),dl=new w({props:{code:"aW5wdXRfaWRzJTIwJTNEJTIwdG9yY2gudGVuc29yKCU1QnRva2VuaXplci5lbmNvZGUoJTIyV2lraXBlZGlhJTIwd2FzJTIwdXNlZCUyMHRvJTIyKSU1RCklMjAlMjAlMjMlMjAlRUIlQjAlQjAlRUMlQjklOTglMjAlRUQlODElQUMlRUElQjglQjAlRUIlOEElOTQlMjAxJUVDJTlFJTg1JUVCJThCJTg4JUVCJThCJUE0",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>input_ids = torch.tensor([tokenizer.encode(<span class="hljs-string">&quot;Wikipedia was used to&quot;</span>)])  <span class="hljs-comment"># \uBC30\uCE58 \uD06C\uAE30\uB294 1\uC785\uB2C8\uB2E4</span>'}}),bl=new w({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>language_id = tokenizer.lang2id[<span class="hljs-string">&quot;en&quot;</span>]  <span class="hljs-comment"># 0</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>langs = torch.tensor([language_id] * input_ids.shape[<span class="hljs-number">1</span>])  <span class="hljs-comment"># torch.tensor([0, 0, 0, ..., 0])</span>

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># (batch_size, sequence_length) shape\uC758 \uD150\uC11C\uAC00 \uB418\uB3C4\uB85D \uB9CC\uB4ED\uB2C8\uB2E4.</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>langs = langs.view(<span class="hljs-number">1</span>, -<span class="hljs-number">1</span>)  <span class="hljs-comment"># \uC774\uC81C [1, sequence_length] shape\uC774 \uB418\uC5C8\uC2B5\uB2C8\uB2E4(\uBC30\uCE58 \uD06C\uAE30\uB294 1\uC785\uB2C8\uB2E4)</span>`}}),Ml=new w({props:{code:"b3V0cHV0cyUyMCUzRCUyMG1vZGVsKGlucHV0X2lkcyUyQyUyMGxhbmdzJTNEbGFuZ3Mp",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>outputs = model(input_ids, langs=langs)'}}),gl=new rl({}),vl=new rl({}),Jl=new rl({}),yl=new rl({}),Ul=new w({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> M2M100ForConditionalGeneration, M2M100Tokenizer

<span class="hljs-meta">&gt;&gt;&gt; </span>en_text = <span class="hljs-string">&quot;Do not meddle in the affairs of wizards, for they are subtle and quick to anger.&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>chinese_text = <span class="hljs-string">&quot;\u4E0D\u8981\u63D2\u624B\u5DEB\u5E2B\u7684\u4E8B\u52D9, \u56E0\u70BA\u4ED6\u5011\u662F\u5FAE\u5999\u7684, \u5F88\u5FEB\u5C31\u6703\u767C\u6012.&quot;</span>

<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = M2M100Tokenizer.from_pretrained(<span class="hljs-string">&quot;facebook/m2m100_418M&quot;</span>, src_lang=<span class="hljs-string">&quot;zh&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = M2M100ForConditionalGeneration.from_pretrained(<span class="hljs-string">&quot;facebook/m2m100_418M&quot;</span>)`}}),_l=new w({props:{code:"ZW5jb2RlZF96aCUyMCUzRCUyMHRva2VuaXplcihjaGluZXNlX3RleHQlMkMlMjByZXR1cm5fdGVuc29ycyUzRCUyMnB0JTIyKQ==",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_zh = tokenizer(chinese_text, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)'}}),Tl=new w({props:{code:"Z2VuZXJhdGVkX3Rva2VucyUyMCUzRCUyMG1vZGVsLmdlbmVyYXRlKCoqZW5jb2RlZF96aCUyQyUyMGZvcmNlZF9ib3NfdG9rZW5faWQlM0R0b2tlbml6ZXIuZ2V0X2xhbmdfaWQoJTIyZW4lMjIpKSUwQXRva2VuaXplci5iYXRjaF9kZWNvZGUoZ2VuZXJhdGVkX3Rva2VucyUyQyUyMHNraXBfc3BlY2lhbF90b2tlbnMlM0RUcnVlKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>generated_tokens = model.generate(**encoded_zh, forced_bos_token_id=tokenizer.get_lang_id(<span class="hljs-string">&quot;en&quot;</span>))
<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer.batch_decode(generated_tokens, skip_special_tokens=<span class="hljs-literal">True</span>)
<span class="hljs-string">&#x27;Do not interfere with the matters of the witches, because they are delicate and will soon be angry.&#x27;</span>`}}),wl=new rl({}),kl=new w({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer, AutoModelForSeq2SeqLM

<span class="hljs-meta">&gt;&gt;&gt; </span>en_text = <span class="hljs-string">&quot;Do not meddle in the affairs of wizards, for they are subtle and quick to anger.&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>fi_text = <span class="hljs-string">&quot;\xC4l\xE4 sekaannu velhojen asioihin, sill\xE4 ne ovat hienovaraisia ja nopeasti vihaisia.&quot;</span>

<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;facebook/mbart-large-50-many-to-many-mmt&quot;</span>, src_lang=<span class="hljs-string">&quot;fi_FI&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = AutoModelForSeq2SeqLM.from_pretrained(<span class="hljs-string">&quot;facebook/mbart-large-50-many-to-many-mmt&quot;</span>)`}}),$l=new w({props:{code:"ZW5jb2RlZF9lbiUyMCUzRCUyMHRva2VuaXplcihlbl90ZXh0JTJDJTIwcmV0dXJuX3RlbnNvcnMlM0QlMjJwdCUyMik=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_en = tokenizer(en_text, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)'}}),jl=new w({props:{code:"Z2VuZXJhdGVkX3Rva2VucyUyMCUzRCUyMG1vZGVsLmdlbmVyYXRlKCoqZW5jb2RlZF9lbiUyQyUyMGZvcmNlZF9ib3NfdG9rZW5faWQlM0R0b2tlbml6ZXIubGFuZ19jb2RlX3RvX2lkKCUyMmVuX1hYJTIyKSklMEF0b2tlbml6ZXIuYmF0Y2hfZGVjb2RlKGdlbmVyYXRlZF90b2tlbnMlMkMlMjBza2lwX3NwZWNpYWxfdG9rZW5zJTNEVHJ1ZSk=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>generated_tokens = model.generate(**encoded_en, forced_bos_token_id=tokenizer.lang_code_to_id(<span class="hljs-string">&quot;en_XX&quot;</span>))
<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer.batch_decode(generated_tokens, skip_special_tokens=<span class="hljs-literal">True</span>)
<span class="hljs-string">&quot;Don&#x27;t interfere with the wizard&#x27;s affairs, because they are subtle, will soon get angry.&quot;</span>`}}),{c(){$=a("meta"),ut=p(),j=a("h1"),D=a("a"),me=a("span"),u(nl.$$.fragment),Ia=p(),pe=a("span"),Za=r("\uB2E4\uAD6D\uC5B4 \uBAA8\uB378 \uCD94\uB860\uD558\uAE30"),ht=p(),u(il.$$.fragment),dt=p(),Q=a("p"),Ca=r(`\u{1F917} Transformers\uC5D0\uB294 \uC5EC\uB7EC \uC885\uB958\uC758 \uB2E4\uAD6D\uC5B4(multilingual) \uBAA8\uB378\uC774 \uC788\uC73C\uBA70, \uB2E8\uC77C \uC5B8\uC5B4(monolingual) \uBAA8\uB378\uACFC \uCD94\uB860 \uC2DC \uC0AC\uC6A9\uBC95\uC774 \uB2E4\uB985\uB2C8\uB2E4.
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