import{S as ui,i as mi,s as hi,e as p,k as m,w as y,t as a,M as _i,c as i,d as s,m as h,x as T,a as c,h as o,b as g,N as Sn,G as t,g as f,y as P,o as k,p as ce,q as v,B as A,v as di,n as fe}from"../../chunks/vendor-hf-doc-builder.js";import{T as ii}from"../../chunks/Tip-hf-doc-builder.js";import{Y as ci}from"../../chunks/Youtube-hf-doc-builder.js";import{I as bt}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{C as S}from"../../chunks/CodeBlock-hf-doc-builder.js";import{C as fi}from"../../chunks/CourseFloatingBanner-hf-doc-builder.js";import{F as bi}from"../../chunks/FrameworkSwitchCourse-hf-doc-builder.js";import"../../chunks/DocNotebookDropdown-hf-doc-builder.js";function $i(E){let l,u;return l=new fi({props:{chapter:2,classNames:"absolute z-10 right-0 top-0",notebooks:[{label:"Google Colab",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/en/chapter2/section2_tf.ipynb"},{label:"Aws Studio",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/master/course/en/chapter2/section2_tf.ipynb"}]}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function ki(E){let l,u;return l=new fi({props:{chapter:2,classNames:"absolute z-10 right-0 top-0",notebooks:[{label:"Google Colab",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/en/chapter2/section2_pt.ipynb"},{label:"Aws Studio",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/master/course/en/chapter2/section2_pt.ipynb"}]}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function vi(E){let l;return{c(){l=a("PyTorch\uB97C \uC0AC\uC6A9\uD558\uB294\uC9C0, TensorFlow\uB97C \uC0AC\uC6A9\uD558\uB294\uC9C0\uC5D0 \uB530\uB77C \uB0B4\uC6A9\uC774 \uC57D\uAC04 \uB2EC\uB77C\uC9C0\uB294 \uCCAB \uBC88\uC9F8 \uC139\uC158\uC785\uB2C8\uB2E4. \uC81C\uBAA9 \uC0C1\uB2E8 \uC2A4\uC704\uCE58\uB97C \uC774\uC6A9\uD574 \uC120\uD638\uD558\uB294 \uD50C\uB7AB\uD3FC\uC744 \uC120\uD0DD\uD558\uC138\uC694!")},l(u){l=o(u,"PyTorch\uB97C \uC0AC\uC6A9\uD558\uB294\uC9C0, TensorFlow\uB97C \uC0AC\uC6A9\uD558\uB294\uC9C0\uC5D0 \uB530\uB77C \uB0B4\uC6A9\uC774 \uC57D\uAC04 \uB2EC\uB77C\uC9C0\uB294 \uCCAB \uBC88\uC9F8 \uC139\uC158\uC785\uB2C8\uB2E4. \uC81C\uBAA9 \uC0C1\uB2E8 \uC2A4\uC704\uCE58\uB97C \uC774\uC6A9\uD574 \uC120\uD638\uD558\uB294 \uD50C\uB7AB\uD3FC\uC744 \uC120\uD0DD\uD558\uC138\uC694!")},m(u,n){f(u,l,n)},d(u){u&&s(l)}}}function ji(E){let l,u;return l=new ci({props:{id:"wVN12smEvqg"}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function Ei(E){let l,u;return l=new ci({props:{id:"1pedAIvTWXk"}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function gi(E){let l,u;return l=new S({props:{code:`raw_inputs = [
    "I've been waiting for a HuggingFace course my whole life.",
    "I hate this so much!",
]
inputs = tokenizer(raw_inputs, padding=True, truncation=True, return_tensors="tf")
print(inputs)`,highlighted:`raw_inputs = [
    <span class="hljs-string">&quot;I&#x27;ve been waiting for a HuggingFace course my whole life.&quot;</span>,
    <span class="hljs-string">&quot;I hate this so much!&quot;</span>,
]
inputs = tokenizer(raw_inputs, padding=<span class="hljs-literal">True</span>, truncation=<span class="hljs-literal">True</span>, return_tensors=<span class="hljs-string">&quot;tf&quot;</span>)
<span class="hljs-built_in">print</span>(inputs)`}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function wi(E){let l,u;return l=new S({props:{code:`raw_inputs = [
    "I've been waiting for a HuggingFace course my whole life.",
    "I hate this so much!",
]
inputs = tokenizer(raw_inputs, padding=True, truncation=True, return_tensors="pt")
print(inputs)`,highlighted:`raw_inputs = [
    <span class="hljs-string">&quot;I&#x27;ve been waiting for a HuggingFace course my whole life.&quot;</span>,
    <span class="hljs-string">&quot;I hate this so much!&quot;</span>,
]
inputs = tokenizer(raw_inputs, padding=<span class="hljs-literal">True</span>, truncation=<span class="hljs-literal">True</span>, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)
<span class="hljs-built_in">print</span>(inputs)`}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function yi(E){let l,u,n,_,b;return _=new S({props:{code:`{
    'input_ids': <tf.Tensor: shape=(2, 16), dtype=int32, numpy=
        array([
            [  101,  1045,  1005,  2310,  2042,  3403,  2005,  1037, 17662, 12172,  2607,  2026,  2878,  2166,  1012,   102],
            [  101,  1045,  5223,  2023,  2061,  2172,   999,   102,     0,     0,     0,     0,     0,     0,     0,     0]
        ], dtype=int32)>, 
    'attention_mask': <tf.Tensor: shape=(2, 16), dtype=int32, numpy=
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            [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
            [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]
        ], dtype=int32)>
}`,highlighted:`{
    <span class="hljs-string">&#x27;input_ids&#x27;</span>: &lt;tf.Tensor: shape=(<span class="hljs-number">2</span>, <span class="hljs-number">16</span>), dtype=int32, numpy=
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        ], dtype=int32)&gt;, 
    <span class="hljs-string">&#x27;attention_mask&#x27;</span>: &lt;tf.Tensor: shape=(<span class="hljs-number">2</span>, <span class="hljs-number">16</span>), dtype=int32, numpy=
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        ], dtype=int32)&gt;
}`}}),{c(){l=p("p"),u=a("TensorFlow tensor\uB85C \uC9C0\uC815\uD588\uC744 \uB54C\uC758 \uACB0\uACFC\uC785\uB2C8\uB2E4."),n=m(),y(_.$$.fragment)},l(d){l=i(d,"P",{});var I=c(l);u=o(I,"TensorFlow tensor\uB85C \uC9C0\uC815\uD588\uC744 \uB54C\uC758 \uACB0\uACFC\uC785\uB2C8\uB2E4."),I.forEach(s),n=h(d),T(_.$$.fragment,d)},m(d,I){f(d,l,I),t(l,u),f(d,n,I),P(_,d,I),b=!0},i(d){b||(v(_.$$.fragment,d),b=!0)},o(d){k(_.$$.fragment,d),b=!1},d(d){d&&s(l),d&&s(n),A(_,d)}}}function Ti(E){let l,u,n,_,b;return _=new S({props:{code:`{
    'input_ids': tensor([
        [  101,  1045,  1005,  2310,  2042,  3403,  2005,  1037, 17662, 12172, 2607,  2026,  2878,  2166,  1012,   102],
        [  101,  1045,  5223,  2023,  2061,  2172,   999,   102,     0,     0,     0,     0,     0,     0,     0,     0]
    ]), 
    'attention_mask': tensor([
        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]
    ])
}`,highlighted:`{
    <span class="hljs-string">&#x27;input_ids&#x27;</span>: tensor([
        [  <span class="hljs-number">101</span>,  <span class="hljs-number">1045</span>,  <span class="hljs-number">1005</span>,  <span class="hljs-number">2310</span>,  <span class="hljs-number">2042</span>,  <span class="hljs-number">3403</span>,  <span class="hljs-number">2005</span>,  <span class="hljs-number">1037</span>, <span class="hljs-number">17662</span>, <span class="hljs-number">12172</span>, <span class="hljs-number">2607</span>,  <span class="hljs-number">2026</span>,  <span class="hljs-number">2878</span>,  <span class="hljs-number">2166</span>,  <span class="hljs-number">1012</span>,   <span class="hljs-number">102</span>],
        [  <span class="hljs-number">101</span>,  <span class="hljs-number">1045</span>,  <span class="hljs-number">5223</span>,  <span class="hljs-number">2023</span>,  <span class="hljs-number">2061</span>,  <span class="hljs-number">2172</span>,   <span class="hljs-number">999</span>,   <span class="hljs-number">102</span>,     <span class="hljs-number">0</span>,     <span class="hljs-number">0</span>,     <span class="hljs-number">0</span>,     <span class="hljs-number">0</span>,     <span class="hljs-number">0</span>,     <span class="hljs-number">0</span>,     <span class="hljs-number">0</span>,     <span class="hljs-number">0</span>]
    ]), 
    <span class="hljs-string">&#x27;attention_mask&#x27;</span>: tensor([
        [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>],
        [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]
    ])
}`}}),{c(){l=p("p"),u=a("PyTorch tensor\uB85C \uC9C0\uC815\uD588\uC744 \uB54C\uC758 \uACB0\uACFC\uC785\uB2C8\uB2E4."),n=m(),y(_.$$.fragment)},l(d){l=i(d,"P",{});var I=c(l);u=o(I,"PyTorch tensor\uB85C \uC9C0\uC815\uD588\uC744 \uB54C\uC758 \uACB0\uACFC\uC785\uB2C8\uB2E4."),I.forEach(s),n=h(d),T(_.$$.fragment,d)},m(d,I){f(d,l,I),t(l,u),f(d,n,I),P(_,d,I),b=!0},i(d){b||(v(_.$$.fragment,d),b=!0)},o(d){k(_.$$.fragment,d),b=!1},d(d){d&&s(l),d&&s(n),A(_,d)}}}function Pi(E){let l,u,n,_,b,d,I,M,C,w,x;return w=new S({props:{code:`from transformers import TFAutoModel

checkpoint = "distilbert-base-uncased-finetuned-sst-2-english"
model = TFAutoModel.from_pretrained(checkpoint)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> TFAutoModel

checkpoint = <span class="hljs-string">&quot;distilbert-base-uncased-finetuned-sst-2-english&quot;</span>
model = TFAutoModel.from_pretrained(checkpoint)`}}),{c(){l=p("p"),u=a("\uD1A0\uD06C\uB098\uC774\uC800\uB97C \uB2E4\uC6B4\uBC1B\uC740 \uBC29\uC2DD\uACFC \uB3D9\uC77C\uD55C \uBC29\uC2DD\uC73C\uB85C \uC0AC\uC804\uD559\uC2B5\uB41C \uBAA8\uB378\uC744 \uB2E4\uC6B4\uBC1B\uC744 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \u{1F917} Transformers\uB294 "),n=p("code"),_=a("from_pretrained"),b=a(" \uBA54\uC11C\uB4DC\uB97C \uAC00\uC9C4 "),d=p("code"),I=a("TFAutoModel"),M=a(" \uD074\uB798\uC2A4\uB97C \uC81C\uACF5\uD569\uB2C8\uB2E4."),C=m(),y(w.$$.fragment)},l($){l=i($,"P",{});var j=c(l);u=o(j,"\uD1A0\uD06C\uB098\uC774\uC800\uB97C \uB2E4\uC6B4\uBC1B\uC740 \uBC29\uC2DD\uACFC \uB3D9\uC77C\uD55C \uBC29\uC2DD\uC73C\uB85C \uC0AC\uC804\uD559\uC2B5\uB41C \uBAA8\uB378\uC744 \uB2E4\uC6B4\uBC1B\uC744 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \u{1F917} Transformers\uB294 "),n=i(j,"CODE",{});var F=c(n);_=o(F,"from_pretrained"),F.forEach(s),b=o(j," \uBA54\uC11C\uB4DC\uB97C \uAC00\uC9C4 "),d=i(j,"CODE",{});var q=c(d);I=o(q,"TFAutoModel"),q.forEach(s),M=o(j," \uD074\uB798\uC2A4\uB97C \uC81C\uACF5\uD569\uB2C8\uB2E4."),j.forEach(s),C=h($),T(w.$$.fragment,$)},m($,j){f($,l,j),t(l,u),t(l,n),t(n,_),t(l,b),t(l,d),t(d,I),t(l,M),f($,C,j),P(w,$,j),x=!0},i($){x||(v(w.$$.fragment,$),x=!0)},o($){k(w.$$.fragment,$),x=!1},d($){$&&s(l),$&&s(C),A(w,$)}}}function Ai(E){let l,u,n,_,b,d,I,M,C,w,x;return w=new S({props:{code:`from transformers import AutoModel

checkpoint = "distilbert-base-uncased-finetuned-sst-2-english"
model = AutoModel.from_pretrained(checkpoint)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoModel

checkpoint = <span class="hljs-string">&quot;distilbert-base-uncased-finetuned-sst-2-english&quot;</span>
model = AutoModel.from_pretrained(checkpoint)`}}),{c(){l=p("p"),u=a("\uD1A0\uD06C\uB098\uC774\uC800\uB97C \uB2E4\uC6B4\uBC1B\uC740 \uBC29\uC2DD\uACFC \uB3D9\uC77C\uD55C \uBC29\uC2DD\uC73C\uB85C \uC0AC\uC804\uD559\uC2B5\uB41C \uBAA8\uB378\uC744 \uB2E4\uC6B4\uBC1B\uC744 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \u{1F917} Transformers\uB294 "),n=p("code"),_=a("from_pretrained"),b=a(" \uBA54\uC11C\uB4DC\uB97C \uAC00\uC9C4 "),d=p("code"),I=a("AutoModel"),M=a(" \uD074\uB798\uC2A4\uB97C \uC81C\uACF5\uD569\uB2C8\uB2E4."),C=m(),y(w.$$.fragment)},l($){l=i($,"P",{});var j=c(l);u=o(j,"\uD1A0\uD06C\uB098\uC774\uC800\uB97C \uB2E4\uC6B4\uBC1B\uC740 \uBC29\uC2DD\uACFC \uB3D9\uC77C\uD55C \uBC29\uC2DD\uC73C\uB85C \uC0AC\uC804\uD559\uC2B5\uB41C \uBAA8\uB378\uC744 \uB2E4\uC6B4\uBC1B\uC744 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \u{1F917} Transformers\uB294 "),n=i(j,"CODE",{});var F=c(n);_=o(F,"from_pretrained"),F.forEach(s),b=o(j," \uBA54\uC11C\uB4DC\uB97C \uAC00\uC9C4 "),d=i(j,"CODE",{});var q=c(d);I=o(q,"AutoModel"),q.forEach(s),M=o(j," \uD074\uB798\uC2A4\uB97C \uC81C\uACF5\uD569\uB2C8\uB2E4."),j.forEach(s),C=h($),T(w.$$.fragment,$)},m($,j){f($,l,j),t(l,u),t(l,n),t(n,_),t(l,b),t(l,d),t(d,I),t(l,M),f($,C,j),P(w,$,j),x=!0},i($){x||(v(w.$$.fragment,$),x=!0)},o($){k(w.$$.fragment,$),x=!1},d($){$&&s(l),$&&s(C),A(w,$)}}}function Ii(E){let l,u,n,_;return l=new S({props:{code:`outputs = model(inputs)
print(outputs.last_hidden_state.shape)`,highlighted:`outputs = model(inputs)
<span class="hljs-built_in">print</span>(outputs.last_hidden_state.shape)`}}),n=new S({props:{code:"(2, 16, 768)",highlighted:'(<span class="hljs-number">2</span>, <span class="hljs-number">16</span>, <span class="hljs-number">768</span>)'}}),{c(){y(l.$$.fragment),u=m(),y(n.$$.fragment)},l(b){T(l.$$.fragment,b),u=h(b),T(n.$$.fragment,b)},m(b,d){P(l,b,d),f(b,u,d),P(n,b,d),_=!0},i(b){_||(v(l.$$.fragment,b),v(n.$$.fragment,b),_=!0)},o(b){k(l.$$.fragment,b),k(n.$$.fragment,b),_=!1},d(b){A(l,b),b&&s(u),A(n,b)}}}function Ci(E){let l,u,n,_;return l=new S({props:{code:`outputs = model(**inputs)
print(outputs.last_hidden_state.shape)`,highlighted:`outputs = model(**inputs)
<span class="hljs-built_in">print</span>(outputs.last_hidden_state.shape)`}}),n=new S({props:{code:"torch.Size([2, 16, 768])",highlighted:'torch.Size([<span class="hljs-number">2</span>, <span class="hljs-number">16</span>, <span class="hljs-number">768</span>])'}}),{c(){y(l.$$.fragment),u=m(),y(n.$$.fragment)},l(b){T(l.$$.fragment,b),u=h(b),T(n.$$.fragment,b)},m(b,d){P(l,b,d),f(b,u,d),P(n,b,d),_=!0},i(b){_||(v(l.$$.fragment,b),v(n.$$.fragment,b),_=!0)},o(b){k(l.$$.fragment,b),k(n.$$.fragment,b),_=!1},d(b){A(l,b),b&&s(u),A(n,b)}}}function Mi(E){let l,u,n,_,b,d,I,M,C,w,x;return w=new S({props:{code:`from transformers import TFAutoModelForSequenceClassification

checkpoint = "distilbert-base-uncased-finetuned-sst-2-english"
model = TFAutoModelForSequenceClassification.from_pretrained(checkpoint)
outputs = model(inputs)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> TFAutoModelForSequenceClassification

checkpoint = <span class="hljs-string">&quot;distilbert-base-uncased-finetuned-sst-2-english&quot;</span>
model = TFAutoModelForSequenceClassification.from_pretrained(checkpoint)
outputs = model(inputs)`}}),{c(){l=p("p"),u=a("\uC774 \uC608\uC81C\uB97C \uC704\uD574\uC11C\uB294 \uBB38\uC7A5\uC744 \uAE0D\uC815 \uB610\uB294 \uBD80\uC815\uC73C\uB85C \uBD84\uB958\uD560 \uC218 \uC788\uAC8C \uD558\uB294 \uC2DC\uD000\uC2A4 \uBD84\uB958 \uD5E4\uB4DC\uB97C \uAC00\uC9C4 \uBAA8\uB378\uC774 \uD544\uC694\uD569\uB2C8\uB2E4. \uB530\uB77C\uC11C "),n=p("code"),_=a("AutoModel"),b=a(" \uD074\uB798\uC2A4\uAC00 \uC544\uB2CC "),d=p("code"),I=a("TFAutoModelForSequenceClassification"),M=a("\uC744 \uC0AC\uC6A9\uD560 \uAC83\uC785\uB2C8\uB2E4."),C=m(),y(w.$$.fragment)},l($){l=i($,"P",{});var j=c(l);u=o(j,"\uC774 \uC608\uC81C\uB97C \uC704\uD574\uC11C\uB294 \uBB38\uC7A5\uC744 \uAE0D\uC815 \uB610\uB294 \uBD80\uC815\uC73C\uB85C \uBD84\uB958\uD560 \uC218 \uC788\uAC8C \uD558\uB294 \uC2DC\uD000\uC2A4 \uBD84\uB958 \uD5E4\uB4DC\uB97C \uAC00\uC9C4 \uBAA8\uB378\uC774 \uD544\uC694\uD569\uB2C8\uB2E4. \uB530\uB77C\uC11C "),n=i(j,"CODE",{});var F=c(n);_=o(F,"AutoModel"),F.forEach(s),b=o(j," \uD074\uB798\uC2A4\uAC00 \uC544\uB2CC "),d=i(j,"CODE",{});var q=c(d);I=o(q,"TFAutoModelForSequenceClassification"),q.forEach(s),M=o(j,"\uC744 \uC0AC\uC6A9\uD560 \uAC83\uC785\uB2C8\uB2E4."),j.forEach(s),C=h($),T(w.$$.fragment,$)},m($,j){f($,l,j),t(l,u),t(l,n),t(n,_),t(l,b),t(l,d),t(d,I),t(l,M),f($,C,j),P(w,$,j),x=!0},i($){x||(v(w.$$.fragment,$),x=!0)},o($){k(w.$$.fragment,$),x=!1},d($){$&&s(l),$&&s(C),A(w,$)}}}function Si(E){let l,u,n,_,b,d,I,M,C,w,x;return w=new S({props:{code:`from transformers import AutoModelForSequenceClassification

checkpoint = "distilbert-base-uncased-finetuned-sst-2-english"
model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
outputs = model(**inputs)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoModelForSequenceClassification

checkpoint = <span class="hljs-string">&quot;distilbert-base-uncased-finetuned-sst-2-english&quot;</span>
model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
outputs = model(**inputs)`}}),{c(){l=p("p"),u=a("\uC774 \uC608\uC81C\uB97C \uC704\uD574\uC11C\uB294 \uBB38\uC7A5\uC744 \uAE0D\uC815 \uB610\uB294 \uBD80\uC815\uC73C\uB85C \uBD84\uB958\uD560 \uC218 \uC788\uAC8C \uD558\uB294 \uC2DC\uD000\uC2A4 \uBD84\uB958 \uD5E4\uB4DC\uB97C \uAC00\uC9C4 \uBAA8\uB378\uC774 \uD544\uC694\uD569\uB2C8\uB2E4. \uB530\uB77C\uC11C "),n=p("code"),_=a("AutoModel"),b=a(" \uD074\uB798\uC2A4\uAC00 \uC544\uB2CC "),d=p("code"),I=a("AutoModelForSequenceClassification"),M=a("\uC744 \uC0AC\uC6A9\uD560 \uAC83\uC785\uB2C8\uB2E4."),C=m(),y(w.$$.fragment)},l($){l=i($,"P",{});var j=c(l);u=o(j,"\uC774 \uC608\uC81C\uB97C \uC704\uD574\uC11C\uB294 \uBB38\uC7A5\uC744 \uAE0D\uC815 \uB610\uB294 \uBD80\uC815\uC73C\uB85C \uBD84\uB958\uD560 \uC218 \uC788\uAC8C \uD558\uB294 \uC2DC\uD000\uC2A4 \uBD84\uB958 \uD5E4\uB4DC\uB97C \uAC00\uC9C4 \uBAA8\uB378\uC774 \uD544\uC694\uD569\uB2C8\uB2E4. \uB530\uB77C\uC11C "),n=i(j,"CODE",{});var F=c(n);_=o(F,"AutoModel"),F.forEach(s),b=o(j," \uD074\uB798\uC2A4\uAC00 \uC544\uB2CC "),d=i(j,"CODE",{});var q=c(d);I=o(q,"AutoModelForSequenceClassification"),q.forEach(s),M=o(j,"\uC744 \uC0AC\uC6A9\uD560 \uAC83\uC785\uB2C8\uB2E4."),j.forEach(s),C=h($),T(w.$$.fragment,$)},m($,j){f($,l,j),t(l,u),t(l,n),t(n,_),t(l,b),t(l,d),t(d,I),t(l,M),f($,C,j),P(w,$,j),x=!0},i($){x||(v(w.$$.fragment,$),x=!0)},o($){k(w.$$.fragment,$),x=!1},d($){$&&s(l),$&&s(C),A(w,$)}}}function xi(E){let l,u;return l=new S({props:{code:"(2, 2)",highlighted:'(<span class="hljs-number">2</span>, <span class="hljs-number">2</span>)'}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function Fi(E){let l,u;return l=new S({props:{code:"torch.Size([2, 2])",highlighted:'torch.Size([<span class="hljs-number">2</span>, <span class="hljs-number">2</span>])'}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function Ni(E){let l,u;return l=new S({props:{code:`<tf.Tensor: shape=(2, 2), dtype=float32, numpy=
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           [ 4.169231 , -3.3464472]], dtype=float32)>`,highlighted:`&lt;tf.Tensor: shape=(<span class="hljs-number">2</span>, <span class="hljs-number">2</span>), dtype=float32, numpy=
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        [ <span class="hljs-number">4.1692</span>, -<span class="hljs-number">3.3464</span>]], grad_fn=&lt;AddmmBackward&gt;)`}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function Di(E){let l,u;return l=new S({props:{code:`import tensorflow as tf

predictions = tf.math.softmax(outputs.logits, axis=-1)
print(predictions)`,highlighted:`<span class="hljs-keyword">import</span> tensorflow <span class="hljs-keyword">as</span> tf

predictions = tf.math.softmax(outputs.logits, axis=-<span class="hljs-number">1</span>)
<span class="hljs-built_in">print</span>(predictions)`}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function Oi(E){let l,u;return l=new S({props:{code:`import torch

predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
print(predictions)`,highlighted:`<span class="hljs-keyword">import</span> torch

predictions = torch.nn.functional.softmax(outputs.logits, dim=-<span class="hljs-number">1</span>)
<span class="hljs-built_in">print</span>(predictions)`}}),{c(){y(l.$$.fragment)},l(n){T(l.$$.fragment,n)},m(n,_){P(l,n,_),u=!0},i(n){u||(v(l.$$.fragment,n),u=!0)},o(n){k(l.$$.fragment,n),u=!1},d(n){A(l,n)}}}function Li(E){let l,u;return l=new S({props:{code:`tf.Tensor(
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)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

classifier = pipeline(<span class="hljs-string">&quot;sentiment-analysis&quot;</span>)
classifier(
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checkpoint = "distilbert-base-uncased-finetuned-sst-2-english"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer

checkpoint = <span class="hljs-string">&quot;distilbert-base-uncased-finetuned-sst-2-english&quot;</span>
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