import{s as gt,o as kt,n as Re}from"../chunks/scheduler.9bc65507.js";import{S as ht,i as $t,g as l,s as o,r as g,A as vt,h as p,f as n,c as a,j as q,u as k,x as _,k as z,y as t,a as m,v as h,d as $,t as v,w as b}from"../chunks/index.707bf1b6.js";import{T as bt}from"../chunks/Tip.c2ecdbf4.js";import{D as V}from"../chunks/Docstring.17db21ae.js";import{C as ut}from"../chunks/CodeBlock.54a9f38d.js";import{E as ft}from"../chunks/ExampleCodeBlock.4f515aa9.js";import{H as qe}from"../chunks/Heading.342b1fa6.js";function xt(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="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}),_(i)!=="svelte-13no23t"&&(i.innerHTML=w)},m(d,c){m(d,i,c)},p:Re,d(d){d&&n(i)}}}function Ct(P){let i,w="sequence pair mask has the following format:",d,c,f;return c=new ut({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=o(),g(c.$$.fragment)},l(r){i=p(r,"P",{"data-svelte-h":!0}),_(i)!=="svelte-16klr56"&&(i.textContent=w),d=a(r),k(c.$$.fragment,r)},m(r,x){m(r,i,x),m(r,d,x),h(c,r,x),f=!0},p:Re,i(r){f||($(c.$$.fragment,r),f=!0)},o(r){v(c.$$.fragment,r),f=!1},d(r){r&&(n(i),n(d)),b(c,r)}}}function wt(P){let i,w="sequence pair mask has the following format:",d,c,f;return c=new ut({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=o(),g(c.$$.fragment)},l(r){i=p(r,"P",{"data-svelte-h":!0}),_(i)!=="svelte-16klr56"&&(i.textContent=w),d=a(r),k(c.$$.fragment,r)},m(r,x){m(r,i,x),m(r,d,x),h(c,r,x),f=!0},p:Re,i(r){f||($(c.$$.fragment,r),f=!0)},o(r){v(c.$$.fragment,r),f=!1},d(r){r&&(n(i),n(d)),b(c,r)}}}function Tt(P){let i,w,d,c,f,r,x,he,G,Ke=`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。`,$e,O,Qe="論文の要約は次のとおりです。",ve,S,et=`<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>`,be,X,tt=`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>`,xe,j,Ce,B,we,u,Z,ze,oe,nt="Runs pre-tokenization with Jieba segmentation tool. It is used in CPM models.",De,y,W,Pe,ae,st=`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,re,ot="<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>",Ae,A,Y,Je,ie,at="Converts a sequence of tokens (strings for sub-words) in a single string.",He,M,R,Ne,le,rt="Create a mask from the two sequences passed to be used in a sequence-pair classification task. An XLNet",Ee,J,Ue,pe,it="If <code>token_ids_1</code> is <code>None</code>, this method only returns the first portion of the mask (0s).",Fe,H,K,Ve,me,lt=`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.`,Te,Q,Me,T,ee,Ge,ce,pt="Runs pre-tokenization with Jieba segmentation tool. It is used in CPM models.",Oe,I,te,Se,de,mt=`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:`,Xe,_e,ct="<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>",Be,L,ne,Ze,fe,dt="Create a mask from the two sequences passed to be used in a sequence-pair classification task. An XLNet",We,N,Ye,ue,_t="If <code>token_ids_1</code> is <code>None</code>, this method only returns the first portion of the mask (0s).",Le,ke,ye;return f=new qe({props:{title:"CPM",local:"cpm",headingTag:"h1"}}),x=new qe({props:{title:"Overview",local:"overview",headingTag:"h2"}}),j=new bt({props:{$$slots:{default:[xt]},$$scope:{ctx:P}}}),B=new qe({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/v4.37.1/src/transformers/models/cpm/tokenization_cpm.py#L38"}}),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/v4.37.1/src/transformers/models/cpm/tokenization_cpm.py#L245",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/v4.37.1/src/transformers/models/cpm/tokenization_cpm.py#L239"}}),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/v4.37.1/src/transformers/models/cpm/tokenization_cpm.py#L300",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 ft({props:{anchor:"transformers.CpmTokenizer.create_token_type_ids_from_sequences.example",$$slots:{default:[Ct]},$$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/v4.37.1/src/transformers/models/cpm/tokenization_cpm.py#L271",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 qe({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/v4.37.1/src/transformers/models/cpm/tokenization_cpm_fast.py#L38"}}),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/v4.37.1/src/transformers/models/cpm/tokenization_cpm_fast.py#L160",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/v4.37.1/src/transformers/models/cpm/tokenization_cpm_fast.py#L186",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>
`}}),N=new ft({props:{anchor:"transformers.CpmTokenizerFast.create_token_type_ids_from_sequences.example",$$slots:{default:[wt]},$$scope:{ctx:P}}}),{c(){i=l("meta"),w=o(),d=l("p"),c=o(),g(f.$$.fragment),r=o(),g(x.$$.fragment),he=o(),G=l("p"),G.innerHTML=Ke,$e=o(),O=l("p"),O.textContent=Qe,ve=o(),S=l("p"),S.innerHTML=et,be=o(),X=l("p"),X.innerHTML=tt,xe=o(),g(j.$$.fragment),Ce=o(),g(B.$$.fragment),we=o(),u=l("div"),g(Z.$$.fragment),ze=o(),oe=l("p"),oe.textContent=nt,De=o(),y=l("div"),g(W.$$.fragment),Pe=o(),ae=l("p"),ae.textContent=st,je=o(),re=l("ul"),re.innerHTML=ot,Ae=o(),A=l("div"),g(Y.$$.fragment),Je=o(),ie=l("p"),ie.textContent=at,He=o(),M=l("div"),g(R.$$.fragment),Ne=o(),le=l("p"),le.textContent=rt,Ee=o(),g(J.$$.fragment),Ue=o(),pe=l("p"),pe.innerHTML=it,Fe=o(),H=l("div"),g(K.$$.fragment),Ve=o(),me=l("p"),me.innerHTML=lt,Te=o(),g(Q.$$.fragment),Me=o(),T=l("div"),g(ee.$$.fragment),Ge=o(),ce=l("p"),ce.textContent=pt,Oe=o(),I=l("div"),g(te.$$.fragment),Se=o(),de=l("p"),de.textContent=mt,Xe=o(),_e=l("ul"),_e.innerHTML=ct,Be=o(),L=l("div"),g(ne.$$.fragment),Ze=o(),fe=l("p"),fe.textContent=dt,We=o(),g(N.$$.fragment),Ye=o(),ue=l("p"),ue.innerHTML=_t,Le=o(),ke=l("p"),this.h()},l(e){const 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