import{s as ht,o as $t,n as Qe}from"../chunks/scheduler.9bc65507.js";import{S as vt,i as bt,g as l,s as a,r as _,A as xt,h as p,f as n,c as o,j as q,u,x as f,k as z,y as t,a as m,v as g,d as k,t as h,w as $}from"../chunks/index.707bf1b6.js";import{T as Ct}from"../chunks/Tip.c2ecdbf4.js";import{D as V}from"../chunks/Docstring.570ddb64.js";import{C as kt}from"../chunks/CodeBlock.54a9f38d.js";import{E as gt}from"../chunks/ExampleCodeBlock.bc2be6bc.js";import{H as De,E as wt}from"../chunks/EditOnGithub.922df6ba.js";function Tt(P){let i,w=`CPM のアーキテクチャは、トークン化方法を除いて GPT-2 と同じです。詳細については、<a href="openai-community/gpt2">GPT-2 ドキュメント</a> を参照してください。
API リファレンス情報。`;return{c(){i=l("p"),i.innerHTML=w},l(d){i=p(d,"P",{"data-svelte-h":!0}),f(i)!=="svelte-hrrftm"&&(i.innerHTML=w)},m(d,c){m(d,i,c)},p:Qe,d(d){d&&n(i)}}}function Mt(P){let i,w="sequence pair mask has the following format:",d,c,v;return c=new kt({props:{code:"MCUyMDAlMjAwJTIwMCUyMDAlMjAwJTIwMCUyMDAlMjAwJTIwMCUyMDAlMjAxJTIwMSUyMDElMjAxJTIwMSUyMDElMjAxJTIwMSUyMDElMEElN0MlMjBmaXJzdCUyMHNlcXVlbmNlJTIwJTIwJTIwJTIwJTdDJTIwc2Vjb25kJTIwc2VxdWVuY2UlMjAlN0M=",highlighted:`0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 1 </span>1<span class="hljs-number"> 1 </span>1<span class="hljs-number"> 1 </span>1<span class="hljs-number"> 1 </span>1 1
| first sequence    | second sequence |`,wrap:!1}}),{c(){i=l("p"),i.textContent=w,d=a(),_(c.$$.fragment)},l(r){i=p(r,"P",{"data-svelte-h":!0}),f(i)!=="svelte-16klr56"&&(i.textContent=w),d=o(r),u(c.$$.fragment,r)},m(r,x){m(r,i,x),m(r,d,x),g(c,r,x),v=!0},p:Qe,i(r){v||(k(c.$$.fragment,r),v=!0)},o(r){h(c.$$.fragment,r),v=!1},d(r){r&&(n(i),n(d)),$(c,r)}}}function Lt(P){let i,w="sequence pair mask has the following format:",d,c,v;return c=new kt({props:{code:"MCUyMDAlMjAwJTIwMCUyMDAlMjAwJTIwMCUyMDAlMjAwJTIwMCUyMDAlMjAxJTIwMSUyMDElMjAxJTIwMSUyMDElMjAxJTIwMSUyMDElMEElN0MlMjBmaXJzdCUyMHNlcXVlbmNlJTIwJTIwJTIwJTIwJTdDJTIwc2Vjb25kJTIwc2VxdWVuY2UlMjAlN0M=",highlighted:`0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 0 </span>0<span class="hljs-number"> 1 </span>1<span class="hljs-number"> 1 </span>1<span class="hljs-number"> 1 </span>1<span class="hljs-number"> 1 </span>1 1
| first sequence    | second sequence |`,wrap:!1}}),{c(){i=l("p"),i.textContent=w,d=a(),_(c.$$.fragment)},l(r){i=p(r,"P",{"data-svelte-h":!0}),f(i)!=="svelte-16klr56"&&(i.textContent=w),d=o(r),u(c.$$.fragment,r)},m(r,x){m(r,i,x),m(r,d,x),g(c,r,x),v=!0},p:Qe,i(r){v||(k(c.$$.fragment,r),v=!0)},o(r){h(c.$$.fragment,r),v=!1},d(r){r&&(n(i),n(d)),$(c,r)}}}function yt(P){let i,w,d,c,v,r,x,$e,G,et=`CPM モデルは、Zhengyan Zhang、Xu Han、Hao Zhou、Pei Ke、Yuxian Gu によって <a href="https://arxiv.org/abs/2012.00413" rel="nofollow">CPM: A Large-scale Generative Chinese Pre-trained Language Model</a> で提案されました。葉徳明、秦裕佳、
Yusheng Su、Haozhe Ji、Jian Guan、Fanchao Qi、Xiaozi Wang、Yanan Zheng、Guoyang Zeng、Huanqi Cao、Shengqi Chen、
Daixuan Li、Zhenbo Sun、Zhiyuan Liu、Minlie Huang、Wentao Han、Jie Tang、Juanzi Li、Xiaoyan Zhu、Maosong Sun。`,ve,O,tt="論文の要約は次のとおりです。",be,S,nt=`<em>事前トレーニングされた言語モデル (PLM) は、さまざまな下流の NLP タスクに有益であることが証明されています。最近ではGPT-3、
1,750億個のパラメータと570GBの学習データを備え、数回の撮影（1枚でも）の容量で大きな注目を集めました
ゼロショット）学習。ただし、GPT-3 を適用して中国語の NLP タスクに対処することは依然として困難です。
GPT-3 の言語は主に英語であり、パラメーターは公開されていません。この技術レポートでは、
大規模な中国語トレーニング データに対する生成的事前トレーニングを備えた中国語事前トレーニング済み言語モデル (CPM)。最高に
私たちの知識の限りでは、26 億のパラメータと 100GB の中国語トレーニング データを備えた CPM は、事前トレーニングされた中国語としては最大のものです。
言語モデルは、会話、エッセイの作成、
クローゼテストと言語理解。広範な実験により、CPM が多くの環境で優れたパフォーマンスを達成できることが実証されています。
少数ショット (ゼロショットでも) 学習の設定での NLP タスク。</em>`,xe,X,st=`このモデルは <a href="https://huggingface.co/canwenxu" rel="nofollow">canwenxu</a> によって提供されました。オリジナルの実装が見つかります
ここ: <a href="https://github.com/TsinghuaAI/CPM-Generate" rel="nofollow">https://github.com/TsinghuaAI/CPM-Generate</a>`,Ce,j,we,B,Te,b,Z,Pe,oe,at="Runs pre-tokenization with Jieba segmentation tool. It is used in CPM models.",je,y,W,Ae,re,ot=`Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
adding special tokens. An XLNet sequence has the following format:`,Je,ie,rt="<li>single sequence: <code>X &lt;sep&gt; &lt;cls&gt;</code></li> <li>pair of sequences: <code>A &lt;sep&gt; B &lt;sep&gt; &lt;cls&gt;</code></li>",He,A,Y,Ee,le,it="Converts a sequence of tokens (strings for sub-words) in a single string.",Ne,M,R,Ue,pe,lt="Create a mask from the two sequences passed to be used in a sequence-pair classification task. An XLNet",Fe,J,Ve,me,pt="If <code>token_ids_1</code> is <code>None</code>, this method only returns the first portion of the mask (0s).",Ge,H,K,Oe,ce,mt=`Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding
special tokens using the tokenizer <code>prepare_for_model</code> method.`,Me,Q,Le,T,ee,Se,de,ct="Runs pre-tokenization with Jieba segmentation tool. It is used in CPM models.",Xe,I,te,Be,fe,dt=`Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
adding special tokens. An XLNet sequence has the following format:`,Ze,_e,ft="<li>single sequence: <code>X &lt;sep&gt; &lt;cls&gt;</code></li> <li>pair of sequences: <code>A &lt;sep&gt; B &lt;sep&gt; &lt;cls&gt;</code></li>",We,L,ne,Ye,ue,_t="Create a mask from the two sequences passed to be used in a sequence-pair classification task. An XLNet",Re,E,Ke,ge,ut="If <code>token_ids_1</code> is <code>None</code>, this method only returns the first portion of the mask (0s).",ye,se,Ie,he,qe;return v=new De({props:{title:"CPM",local:"cpm",headingTag:"h1"}}),x=new De({props:{title:"Overview",local:"overview",headingTag:"h2"}}),j=new Ct({props:{$$slots:{default:[Tt]},$$scope:{ctx:P}}}),B=new De({props:{title:"CpmTokenizer",local:"transformers.CpmTokenizer",headingTag:"h2"}}),Z=new V({props:{name:"class transformers.CpmTokenizer",anchor:"transformers.CpmTokenizer",parameters:[{name:"vocab_file",val:""},{name:"do_lower_case",val:" = False"},{name:"remove_space",val:" = True"},{name:"keep_accents",val:" = False"},{name:"bos_token",val:" = '<s>'"},{name:"eos_token",val:" = '</s>'"},{name:"unk_token",val:" = '<unk>'"},{name:"sep_token",val:" = '<sep>'"},{name:"pad_token",val:" = '<pad>'"},{name:"cls_token",val:" = '<cls>'"},{name:"mask_token",val:" = '<mask>'"},{name:"additional_special_tokens",val:" = ['<eop>', '<eod>']"},{name:"sp_model_kwargs",val:": Optional = None"},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm.py#L32"}}),W=new V({props:{name:"build_inputs_with_special_tokens",anchor:"transformers.CpmTokenizer.build_inputs_with_special_tokens",parameters:[{name:"token_ids_0",val:": List"},{name:"token_ids_1",val:": Optional = None"}],parametersDescription:[{anchor:"transformers.CpmTokenizer.build_inputs_with_special_tokens.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
List of IDs to which the special tokens will be added.`,name:"token_ids_0"},{anchor:"transformers.CpmTokenizer.build_inputs_with_special_tokens.token_ids_1",description:`<strong>token_ids_1</strong> (<code>List[int]</code>, <em>optional</em>) &#x2014;
Optional second list of IDs for sequence pairs.`,name:"token_ids_1"}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm.py#L238",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>List of <a href="../glossary#input-ids">input IDs</a> with the appropriate special tokens.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>List[int]</code></p>
`}}),Y=new V({props:{name:"convert_tokens_to_string",anchor:"transformers.CpmTokenizer.convert_tokens_to_string",parameters:[{name:"tokens",val:""}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm.py#L232"}}),R=new V({props:{name:"create_token_type_ids_from_sequences",anchor:"transformers.CpmTokenizer.create_token_type_ids_from_sequences",parameters:[{name:"token_ids_0",val:": List"},{name:"token_ids_1",val:": Optional = None"}],parametersDescription:[{anchor:"transformers.CpmTokenizer.create_token_type_ids_from_sequences.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
List of IDs.`,name:"token_ids_0"},{anchor:"transformers.CpmTokenizer.create_token_type_ids_from_sequences.token_ids_1",description:`<strong>token_ids_1</strong> (<code>List[int]</code>, <em>optional</em>) &#x2014;
Optional second list of IDs for sequence pairs.`,name:"token_ids_1"}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm.py#L293",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>List of <a href="../glossary#token-type-ids">token type IDs</a> according to the given sequence(s).</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>List[int]</code></p>
`}}),J=new gt({props:{anchor:"transformers.CpmTokenizer.create_token_type_ids_from_sequences.example",$$slots:{default:[Mt]},$$scope:{ctx:P}}}),K=new V({props:{name:"get_special_tokens_mask",anchor:"transformers.CpmTokenizer.get_special_tokens_mask",parameters:[{name:"token_ids_0",val:": List"},{name:"token_ids_1",val:": Optional = None"},{name:"already_has_special_tokens",val:": bool = False"}],parametersDescription:[{anchor:"transformers.CpmTokenizer.get_special_tokens_mask.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
List of IDs.`,name:"token_ids_0"},{anchor:"transformers.CpmTokenizer.get_special_tokens_mask.token_ids_1",description:`<strong>token_ids_1</strong> (<code>List[int]</code>, <em>optional</em>) &#x2014;
Optional second list of IDs for sequence pairs.`,name:"token_ids_1"},{anchor:"transformers.CpmTokenizer.get_special_tokens_mask.already_has_special_tokens",description:`<strong>already_has_special_tokens</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) &#x2014;
Whether or not the token list is already formatted with special tokens for the model.`,name:"already_has_special_tokens"}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm.py#L264",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>List[int]</code></p>
`}}),Q=new De({props:{title:"CpmTokenizerFast",local:"transformers.CpmTokenizerFast",headingTag:"h2"}}),ee=new V({props:{name:"class transformers.CpmTokenizerFast",anchor:"transformers.CpmTokenizerFast",parameters:[{name:"vocab_file",val:" = None"},{name:"tokenizer_file",val:" = None"},{name:"do_lower_case",val:" = False"},{name:"remove_space",val:" = True"},{name:"keep_accents",val:" = False"},{name:"bos_token",val:" = '<s>'"},{name:"eos_token",val:" = '</s>'"},{name:"unk_token",val:" = '<unk>'"},{name:"sep_token",val:" = '<sep>'"},{name:"pad_token",val:" = '<pad>'"},{name:"cls_token",val:" = '<cls>'"},{name:"mask_token",val:" = '<mask>'"},{name:"additional_special_tokens",val:" = ['<eop>', '<eod>']"},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm_fast.py#L29"}}),te=new V({props:{name:"build_inputs_with_special_tokens",anchor:"transformers.CpmTokenizerFast.build_inputs_with_special_tokens",parameters:[{name:"token_ids_0",val:": List"},{name:"token_ids_1",val:": Optional = None"}],parametersDescription:[{anchor:"transformers.CpmTokenizerFast.build_inputs_with_special_tokens.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
List of IDs to which the special tokens will be added.`,name:"token_ids_0"},{anchor:"transformers.CpmTokenizerFast.build_inputs_with_special_tokens.token_ids_1",description:`<strong>token_ids_1</strong> (<code>List[int]</code>, <em>optional</em>) &#x2014;
Optional second list of IDs for sequence pairs.`,name:"token_ids_1"}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm_fast.py#L151",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>List of <a href="../glossary#input-ids">input IDs</a> with the appropriate special tokens.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>List[int]</code></p>
`}}),ne=new V({props:{name:"create_token_type_ids_from_sequences",anchor:"transformers.CpmTokenizerFast.create_token_type_ids_from_sequences",parameters:[{name:"token_ids_0",val:": List"},{name:"token_ids_1",val:": Optional = None"}],parametersDescription:[{anchor:"transformers.CpmTokenizerFast.create_token_type_ids_from_sequences.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
List of IDs.`,name:"token_ids_0"},{anchor:"transformers.CpmTokenizerFast.create_token_type_ids_from_sequences.token_ids_1",description:`<strong>token_ids_1</strong> (<code>List[int]</code>, <em>optional</em>) &#x2014;
Optional second list of IDs for sequence pairs.`,name:"token_ids_1"}],source:"https://github.com/huggingface/transformers/blob/main/src/transformers/models/cpm/tokenization_cpm_fast.py#L177",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>List of <a href="../glossary#token-type-ids">token type IDs</a> according to the given sequence(s).</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>List[int]</code></p>
`}}),E=new gt({props:{anchor:"transformers.CpmTokenizerFast.create_token_type_ids_from_sequences.example",$$slots:{default:[Lt]},$$scope:{ctx:P}}}),se=new wt({props:{source:"https://github.com/huggingface/transformers/blob/main/docs/source/ja/model_doc/cpm.md"}}),{c(){i=l("meta"),w=a(),d=l("p"),c=a(),_(v.$$.fragment),r=a(),_(x.$$.fragment),$e=a(),G=l("p"),G.innerHTML=et,ve=a(),O=l("p"),O.textContent=tt,be=a(),S=l("p"),S.innerHTML=nt,xe=a(),X=l("p"),X.innerHTML=st,Ce=a(),_(j.$$.fragment),we=a(),_(B.$$.fragment),Te=a(),b=l("div"),_(Z.$$.fragment),Pe=a(),oe=l("p"),oe.textContent=at,je=a(),y=l("div"),_(W.$$.fragment),Ae=a(),re=l("p"),re.textContent=ot,Je=a(),ie=l("ul"),ie.innerHTML=rt,He=a(),A=l("div"),_(Y.$$.fragment),Ee=a(),le=l("p"),le.textContent=it,Ne=a(),M=l("div"),_(R.$$.fragment),Ue=a(),pe=l("p"),pe.textContent=lt,Fe=a(),_(J.$$.fragment),Ve=a(),me=l("p"),me.innerHTML=pt,Ge=a(),H=l("div"),_(K.$$.fragment),Oe=a(),ce=l("p"),ce.innerHTML=mt,Me=a(),_(Q.$$.fragment),Le=a(),T=l("div"),_(ee.$$.fragment),Se=a(),de=l("p"),de.textContent=ct,Xe=a(),I=l("div"),_(te.$$.fragment),Be=a(),fe=l("p"),fe.textContent=dt,Ze=a(),_e=l("ul"),_e.innerHTML=ft,We=a(),L=l("div"),_(ne.$$.fragment),Ye=a(),ue=l("p"),ue.textContent=_t,Re=a(),_(E.$$.fragment),Ke=a(),ge=l("p"),ge.innerHTML=ut,ye=a(),_(se.$$.fragment),Ie=a(),he=l("p"),this.h()},l(e){const s=xt("svelte-u9bgzb",document.head);i=p(s,"META",{name:!0,content:!0}),s.forEach(n),w=o(e),d=p(e,"P",{}),q(d).forEach(n),c=o(e),u(v.$$.fragment,e),r=o(e),u(x.$$.fragment,e),$e=o(e),G=p(e,"P",{"data-svelte-h":!0}),f(G)!=="svelte-1xt3ugf"&&(G.innerHTML=et),ve=o(e),O=p(e,"P",{"data-svelte-h":!0}),f(O)!=="svelte-1cv3nri"&&(O.textContent=tt),be=o(e),S=p(e,"P",{"data-svelte-h":!0}),f(S)!=="svelte-7anbpp"&&(S.innerHTML=nt),xe=o(e),X=p(e,"P",{"data-svelte-h":!0}),f(X)!=="svelte-16rqoku"&&(X.innerHTML=st),Ce=o(e),u(j.$$.fragment,e),we=o(e),u(B.$$.fragment,e),Te=o(e),b=p(e,"DIV",{class:!0});var C=q(b);u(Z.$$.fragment,C),Pe=o(C),oe=p(C,"P",{"data-svelte-h":!0}),f(oe)!=="svelte-ejpd0l"&&(oe.textContent=at),je=o(C),y=p(C,"DIV",{class:!0});var D=q(y);u(W.$$.fragment,D),Ae=o(D),re=p(D,"P",{"data-svelte-h":!0}),f(re)!=="svelte-1dgk30w"&&(re.textContent=ot),Je=o(D),ie=p(D,"UL",{"data-svelte-h":!0}),f(ie)!=="svelte-zi1mnq"&&(ie.innerHTML=rt),D.forEach(n),He=o(C),A=p(C,"DIV",{class:!0});var ae=q(A);u(Y.$$.fragment,ae),Ee=o(ae),le=p(ae,"P",{"data-svelte-h":!0}),f(le)!=="svelte-1ne8awa"&&(le.textContent=it),ae.forEach(n),Ne=o(C),M=p(C,"DIV",{class:!0});var N=q(M);u(R.$$.fragment,N),Ue=o(N),pe=p(N,"P",{"data-svelte-h":!0}),f(pe)!=="svelte-1nwvqaq"&&(pe.textContent=lt),Fe=o(N),u(J.$$.fragment,N),Ve=o(N),me=p(N,"P",{"data-svelte-h":!0}),f(me)!=="svelte-owoxgn"&&(me.innerHTML=pt),N.forEach(n),Ge=o(C),H=p(C,"DIV",{class:!0});var ze=q(H);u(K.$$.fragment,ze),Oe=o(ze),ce=p(ze,"P",{"data-svelte-h":!0}),f(ce)!=="svelte-1f4f5kp"&&(ce.innerHTML=mt),ze.forEach(n),C.forEach(n),Me=o(e),u(Q.$$.fragment,e),Le=o(e),T=p(e,"DIV",{class:!0});var U=q(T);u(ee.$$.fragment,U),Se=o(U),de=p(U,"P",{"data-svelte-h":!0}),f(de)!=="svelte-ejpd0l"&&(de.textContent=ct),Xe=o(U),I=p(U,"DIV",{class:!0});var ke=q(I);u(te.$$.fragment,ke),Be=o(ke),fe=p(ke,"P",{"data-svelte-h":!0}),f(fe)!=="svelte-1dgk30w"&&(fe.textContent=dt),Ze=o(ke),_e=p(ke,"UL",{"data-svelte-h":!0}),f(_e)!=="svelte-zi1mnq"&&(_e.innerHTML=ft),ke.forEach(n),We=o(U),L=p(U,"DIV",{class:!0});var F=q(L);u(ne.$$.fragment,F),Ye=o(F),ue=p(F,"P",{"data-svelte-h":!0}),f(ue)!=="svelte-1nwvqaq"&&(ue.textContent=_t),Re=o(F),u(E.$$.fragment,F),Ke=o(F),ge=p(F,"P",{"data-svelte-h":!0}),f(ge)!=="svelte-owoxgn"&&(ge.innerHTML=ut),F.forEach(n),U.forEach(n),ye=o(e),u(se.$$.fragment,e),Ie=o(e),he=p(e,"P",{}),q(he).forEach(n),this.h()},h(){z(i,"name","hf:doc:metadata"),z(i,"content",It),z(y,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),z(A,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),z(M,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),z(H,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),z(b,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),z(I,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),z(L,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),z(T,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8")},m(e,s){t(document.head,i),m(e,w,s),m(e,d,s),m(e,c,s),g(v,e,s),m(e,r,s),g(x,e,s),m(e,$e,s),m(e,G,s),m(e,ve,s),m(e,O,s),m(e,be,s),m(e,S,s),m(e,xe,s),m(e,X,s),m(e,Ce,s),g(j,e,s),m(e,we,s),g(B,e,s),m(e,Te,s),m(e,b,s),g(Z,b,null),t(b,Pe),t(b,oe),t(b,je),t(b,y),g(W,y,null),t(y,Ae),t(y,re),t(y,Je),t(y,ie),t(b,He),t(b,A),g(Y,A,null),t(A,Ee),t(A,le),t(b,Ne),t(b,M),g(R,M,null),t(M,Ue),t(M,pe),t(M,Fe),g(J,M,null),t(M,Ve),t(M,me),t(b,Ge),t(b,H),g(K,H,null),t(H,Oe),t(H,ce),m(e,Me,s),g(Q,e,s),m(e,Le,s),m(e,T,s),g(ee,T,null),t(T,Se),t(T,de),t(T,Xe),t(T,I),g(te,I,null),t(I,Be),t(I,fe),t(I,Ze),t(I,_e),t(T,We),t(T,L),g(ne,L,null),t(L,Ye),t(L,ue),t(L,Re),g(E,L,null),t(L,Ke),t(L,ge),m(e,ye,s),g(se,e,s),m(e,Ie,s),m(e,he,s),qe=!0},p(e,[s]){const C={};s&2&&(C.$$scope={dirty:s,ctx:e}),j.$set(C);const D={};s&2&&(D.$$scope={dirty:s,ctx:e}),J.$set(D);const ae={};s&2&&(ae.$$scope={dirty:s,ctx:e}),E.$set(ae)},i(e){qe||(k(v.$$.fragment,e),k(x.$$.fragment,e),k(j.$$.fragment,e),k(B.$$.fragment,e),k(Z.$$.fragment,e),k(W.$$.fragment,e),k(Y.$$.fragment,e),k(R.$$.fragment,e),k(J.$$.fragment,e),k(K.$$.fragment,e),k(Q.$$.fragment,e),k(ee.$$.fragment,e),k(te.$$.fragment,e),k(ne.$$.fragment,e),k(E.$$.fragment,e),k(se.$$.fragment,e),qe=!0)},o(e){h(v.$$.fragment,e),h(x.$$.fragment,e),h(j.$$.fragment,e),h(B.$$.fragment,e),h(Z.$$.fragment,e),h(W.$$.fragment,e),h(Y.$$.fragment,e),h(R.$$.fragment,e),h(J.$$.fragment,e),h(K.$$.fragment,e),h(Q.$$.fragment,e),h(ee.$$.fragment,e),h(te.$$.fragment,e),h(ne.$$.fragment,e),h(E.$$.fragment,e),h(se.$$.fragment,e),qe=!1},d(e){e&&(n(w),n(d),n(c),n(r),n($e),n(G),n(ve),n(O),n(be),n(S),n(xe),n(X),n(Ce),n(we),n(Te),n(b),n(Me),n(Le),n(T),n(ye),n(Ie),n(he)),n(i),$(v,e),$(x,e),$(j,e),$(B,e),$(Z),$(W),$(Y),$(R),$(J),$(K),$(Q,e),$(ee),$(te),$(ne),$(E),$(se,e)}}}const It='{"title":"CPM","local":"cpm","sections":[{"title":"Overview","local":"overview","sections":[],"depth":2},{"title":"CpmTokenizer","local":"transformers.CpmTokenizer","sections":[],"depth":2},{"title":"CpmTokenizerFast","local":"transformers.CpmTokenizerFast","sections":[],"depth":2}],"depth":1}';function qt(P){return $t(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class Et extends vt{constructor(i){super(),bt(this,i,qt,yt,ht,{})}}export{Et as component};
