import{s as Rn,o as En,n as E}from"../chunks/scheduler.6062bdaf.js";import{S as Nn,i as Zn,g as d,s as o,r as g,A as Wn,h as p,f as t,c as r,j as U,u as m,x as C,k as J,y as c,a as i,v as h,d as u,t as M,w as f,m as Dn,n as kn}from"../chunks/index.4bca734e.js";import{T as In}from"../chunks/Tip.b9ac1f03.js";import{D as w}from"../chunks/Docstring.d7918b6d.js";import{C as X}from"../chunks/CodeBlock.fa01571c.js";import{E as F}from"../chunks/ExampleCodeBlock.d27cbfa4.js";import{H as $,E as Gn}from"../chunks/EditOnGithub.74ab2baa.js";function Yn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"ZnJvbSUyMGh1Z2dpbmdmYWNlX2h1Yi5yZXBvY2FyZCUyMGltcG9ydCUyMFJlcG9DYXJkJTBBdGV4dCUyMCUzRCUyMCcnJyUwQS0tLSUwQWxhbmd1YWdlJTNBJTIwZW4lMEFsaWNlbnNlJTNBJTIwbWl0JTBBLS0tJTBBJTIzJTIwTXklMjByZXBvJTBBJycnJTBBY2FyZCUyMCUzRCUyMFJlcG9DYXJkKHRleHQpJTBBY2FyZC5kYXRhLnRvX2RpY3QoKSUwQWNhcmQudGV4dCUwQQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub.repocard <span class="hljs-keyword">import</span> RepoCard
<span class="hljs-meta">&gt;&gt;&gt; </span>text = <span class="hljs-string">&#x27;&#x27;&#x27;
<span class="hljs-meta">... </span>---
<span class="hljs-meta">... </span>language: en
<span class="hljs-meta">... </span>license: mit
<span class="hljs-meta">... </span>---
...
<span class="hljs-meta">... </span># My repo
<span class="hljs-meta">... </span>&#x27;&#x27;&#x27;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>card = RepoCard(text)
<span class="hljs-meta">&gt;&gt;&gt; </span>card.data.to_dict()
{<span class="hljs-string">&#x27;language&#x27;</span>: <span class="hljs-string">&#x27;en&#x27;</span>, <span class="hljs-string">&#x27;license&#x27;</span>: <span class="hljs-string">&#x27;mit&#x27;</span>}
<span class="hljs-meta">&gt;&gt;&gt; </span>card.text
<span class="hljs-string">&#x27;\\n# My repo\\n&#x27;</span>
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Sn(x){let n,y,j=`<li><a href="https://docs.python.org/3/library/exceptions.html#ValueError" rel="nofollow"><code>ValueError</code></a>
when the content of the repo card metadata is not a dictionary.</li>`;return{c(){n=Dn(`Raises the following error:
`),y=d("ul"),y.innerHTML=j},l(s){n=kn(s,`Raises the following error:
`),y=p(s,"UL",{"data-svelte-h":!0}),C(y)!=="svelte-1ewksj3"&&(y.innerHTML=j)},m(s,_){i(s,n,_),i(s,y,_)},p:E,d(s){s&&(t(n),t(y))}}}function Bn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"ZnJvbSUyMGh1Z2dpbmdmYWNlX2h1Yi5yZXBvY2FyZCUyMGltcG9ydCUyMFJlcG9DYXJkJTBBY2FyZCUyMCUzRCUyMFJlcG9DYXJkLmxvYWQoJTIybmF0ZXJhdyUyRmZvb2QlMjIpJTBBYXNzZXJ0JTIwY2FyZC5kYXRhLnRhZ3MlMjAlM0QlM0QlMjAlNUIlMjJnZW5lcmF0ZWRfZnJvbV90cmFpbmVyJTIyJTJDJTIwJTIyaW1hZ2UtY2xhc3NpZmljYXRpb24lMjIlMkMlMjAlMjJweXRvcmNoJTIyJTVEJTBB",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub.repocard <span class="hljs-keyword">import</span> RepoCard
<span class="hljs-meta">&gt;&gt;&gt; </span>card = RepoCard.load(<span class="hljs-string">&quot;nateraw/food&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">assert</span> card.data.tags == [<span class="hljs-string">&quot;generated_from_trainer&quot;</span>, <span class="hljs-string">&quot;image-classification&quot;</span>, <span class="hljs-string">&quot;pytorch&quot;</span>]
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Qn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"ZnJvbSUyMGh1Z2dpbmdmYWNlX2h1Yi5yZXBvY2FyZCUyMGltcG9ydCUyMFJlcG9DYXJkJTBBY2FyZCUyMCUzRCUyMFJlcG9DYXJkKCUyMi0tLSU1Q25sYW5ndWFnZSUzQSUyMGVuJTVDbi0tLSU1Q24lMjMlMjBUaGlzJTIwaXMlMjBhJTIwdGVzdCUyMHJlcG8lMjBjYXJkJTIyKSUwQWNhcmQuc2F2ZSglMjIlMkZ0bXAlMkZ0ZXN0Lm1kJTIyKSUwQQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub.repocard <span class="hljs-keyword">import</span> RepoCard
<span class="hljs-meta">&gt;&gt;&gt; </span>card = RepoCard(<span class="hljs-string">&quot;---\\nlanguage: en\\n---\\n# This is a test repo card&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card.save(<span class="hljs-string">&quot;/tmp/test.md&quot;</span>)
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Fn(x){let n,y,j=`<li><a href="https://docs.python.org/3/library/exceptions.html#ValueError" rel="nofollow"><code>ValueError</code></a>
if the card fails validation checks.</li> <li><a href="https://requests.readthedocs.io/en/latest/api/#requests.HTTPError" rel="nofollow"><code>HTTPError</code></a>
if the request to the Hub API fails for any other reason.</li>`;return{c(){n=Dn(`Raises the following errors:
`),y=d("ul"),y.innerHTML=j},l(s){n=kn(s,`Raises the following errors:
`),y=p(s,"UL",{"data-svelte-h":!0}),C(y)!=="svelte-brxevo"&&(y.innerHTML=j)},m(s,_){i(s,n,_),i(s,y,_)},p:E,d(s){s&&(t(n),t(y))}}}function Xn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> ModelCard, ModelCardData, EvalResult

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Using the Default Template</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data = ModelCardData(
<span class="hljs-meta">... </span>    language=<span class="hljs-string">&#x27;en&#x27;</span>,
<span class="hljs-meta">... </span>    license=<span class="hljs-string">&#x27;mit&#x27;</span>,
<span class="hljs-meta">... </span>    library_name=<span class="hljs-string">&#x27;timm&#x27;</span>,
<span class="hljs-meta">... </span>    tags=[<span class="hljs-string">&#x27;image-classification&#x27;</span>, <span class="hljs-string">&#x27;resnet&#x27;</span>],
<span class="hljs-meta">... </span>    datasets=[<span class="hljs-string">&#x27;beans&#x27;</span>],
<span class="hljs-meta">... </span>    metrics=[<span class="hljs-string">&#x27;accuracy&#x27;</span>],
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card = ModelCard.from_template(
<span class="hljs-meta">... </span>    card_data,
<span class="hljs-meta">... </span>    model_description=<span class="hljs-string">&#x27;This model does x + y...&#x27;</span>
<span class="hljs-meta">... </span>)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Including Evaluation Results</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data = ModelCardData(
<span class="hljs-meta">... </span>    language=<span class="hljs-string">&#x27;en&#x27;</span>,
<span class="hljs-meta">... </span>    tags=[<span class="hljs-string">&#x27;image-classification&#x27;</span>, <span class="hljs-string">&#x27;resnet&#x27;</span>],
<span class="hljs-meta">... </span>    eval_results=[
<span class="hljs-meta">... </span>        EvalResult(
<span class="hljs-meta">... </span>            task_type=<span class="hljs-string">&#x27;image-classification&#x27;</span>,
<span class="hljs-meta">... </span>            dataset_type=<span class="hljs-string">&#x27;beans&#x27;</span>,
<span class="hljs-meta">... </span>            dataset_name=<span class="hljs-string">&#x27;Beans&#x27;</span>,
<span class="hljs-meta">... </span>            metric_type=<span class="hljs-string">&#x27;accuracy&#x27;</span>,
<span class="hljs-meta">... </span>            metric_value=<span class="hljs-number">0.9</span>,
<span class="hljs-meta">... </span>        ),
<span class="hljs-meta">... </span>    ],
<span class="hljs-meta">... </span>    model_name=<span class="hljs-string">&#x27;my-cool-model&#x27;</span>,
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card = ModelCard.from_template(card_data)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Using a Custom Template</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data = ModelCardData(
<span class="hljs-meta">... </span>    language=<span class="hljs-string">&#x27;en&#x27;</span>,
<span class="hljs-meta">... </span>    tags=[<span class="hljs-string">&#x27;image-classification&#x27;</span>, <span class="hljs-string">&#x27;resnet&#x27;</span>]
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card = ModelCard.from_template(
<span class="hljs-meta">... </span>    card_data=card_data,
<span class="hljs-meta">... </span>    template_path=<span class="hljs-string">&#x27;./src/huggingface_hub/templates/modelcard_template.md&#x27;</span>,
<span class="hljs-meta">... </span>    custom_template_var=<span class="hljs-string">&#x27;custom value&#x27;</span>,  <span class="hljs-comment"># will be replaced in template if it exists</span>
<span class="hljs-meta">... </span>)
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Vn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"ZnJvbSUyMGh1Z2dpbmdmYWNlX2h1YiUyMGltcG9ydCUyME1vZGVsQ2FyZERhdGElMEFjYXJkX2RhdGElMjAlM0QlMjBNb2RlbENhcmREYXRhKCUwQSUyMCUyMCUyMCUyMGxhbmd1YWdlJTNEJTIyZW4lMjIlMkMlMEElMjAlMjAlMjAlMjBsaWNlbnNlJTNEJTIybWl0JTIyJTJDJTBBJTIwJTIwJTIwJTIwbGlicmFyeV9uYW1lJTNEJTIydGltbSUyMiUyQyUwQSUyMCUyMCUyMCUyMHRhZ3MlM0QlNUInaW1hZ2UtY2xhc3NpZmljYXRpb24nJTJDJTIwJ3Jlc25ldCclNUQlMkMlMEEpJTBBY2FyZF9kYXRhLnRvX2RpY3QoKSUwQQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> ModelCardData
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data = ModelCardData(
<span class="hljs-meta">... </span>    language=<span class="hljs-string">&quot;en&quot;</span>,
<span class="hljs-meta">... </span>    license=<span class="hljs-string">&quot;mit&quot;</span>,
<span class="hljs-meta">... </span>    library_name=<span class="hljs-string">&quot;timm&quot;</span>,
<span class="hljs-meta">... </span>    tags=[<span class="hljs-string">&#x27;image-classification&#x27;</span>, <span class="hljs-string">&#x27;resnet&#x27;</span>],
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data.to_dict()
{<span class="hljs-string">&#x27;language&#x27;</span>: <span class="hljs-string">&#x27;en&#x27;</span>, <span class="hljs-string">&#x27;license&#x27;</span>: <span class="hljs-string">&#x27;mit&#x27;</span>, <span class="hljs-string">&#x27;library_name&#x27;</span>: <span class="hljs-string">&#x27;timm&#x27;</span>, <span class="hljs-string">&#x27;tags&#x27;</span>: [<span class="hljs-string">&#x27;image-classification&#x27;</span>, <span class="hljs-string">&#x27;resnet&#x27;</span>]}
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Hn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> DatasetCard, DatasetCardData

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Using the Default Template</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data = DatasetCardData(
<span class="hljs-meta">... </span>    language=<span class="hljs-string">&#x27;en&#x27;</span>,
<span class="hljs-meta">... </span>    license=<span class="hljs-string">&#x27;mit&#x27;</span>,
<span class="hljs-meta">... </span>    annotations_creators=<span class="hljs-string">&#x27;crowdsourced&#x27;</span>,
<span class="hljs-meta">... </span>    task_categories=[<span class="hljs-string">&#x27;text-classification&#x27;</span>],
<span class="hljs-meta">... </span>    task_ids=[<span class="hljs-string">&#x27;sentiment-classification&#x27;</span>, <span class="hljs-string">&#x27;text-scoring&#x27;</span>],
<span class="hljs-meta">... </span>    multilinguality=<span class="hljs-string">&#x27;monolingual&#x27;</span>,
<span class="hljs-meta">... </span>    pretty_name=<span class="hljs-string">&#x27;My Text Classification Dataset&#x27;</span>,
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card = DatasetCard.from_template(
<span class="hljs-meta">... </span>    card_data,
<span class="hljs-meta">... </span>    pretty_name=card_data.pretty_name,
<span class="hljs-meta">... </span>)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Using a Custom Template</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data = DatasetCardData(
<span class="hljs-meta">... </span>    language=<span class="hljs-string">&#x27;en&#x27;</span>,
<span class="hljs-meta">... </span>    license=<span class="hljs-string">&#x27;mit&#x27;</span>,
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card = DatasetCard.from_template(
<span class="hljs-meta">... </span>    card_data=card_data,
<span class="hljs-meta">... </span>    template_path=<span class="hljs-string">&#x27;./src/huggingface_hub/templates/datasetcard_template.md&#x27;</span>,
<span class="hljs-meta">... </span>    custom_template_var=<span class="hljs-string">&#x27;custom value&#x27;</span>,  <span class="hljs-comment"># will be replaced in template if it exists</span>
<span class="hljs-meta">... </span>)
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Ln(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"ZnJvbSUyMGh1Z2dpbmdmYWNlX2h1YiUyMGltcG9ydCUyMFNwYWNlQ2FyZERhdGElMEFjYXJkX2RhdGElMjAlM0QlMjBTcGFjZUNhcmREYXRhKCUwQSUyMCUyMCUyMCUyMHRpdGxlJTNEJTIyRHJlYW1ib290aCUyMFRyYWluaW5nJTIyJTJDJTBBJTIwJTIwJTIwJTIwbGljZW5zZSUzRCUyMm1pdCUyMiUyQyUwQSUyMCUyMCUyMCUyMHNkayUzRCUyMmdyYWRpbyUyMiUyQyUwQSUyMCUyMCUyMCUyMGR1cGxpY2F0ZWRfZnJvbSUzRCUyMm11bHRpbW9kYWxhcnQlMkZkcmVhbWJvb3RoLXRyYWluaW5nJTIyJTBBKSUwQWNhcmRfZGF0YS50b19kaWN0KCk=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> SpaceCardData
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data = SpaceCardData(
<span class="hljs-meta">... </span>    title=<span class="hljs-string">&quot;Dreambooth Training&quot;</span>,
<span class="hljs-meta">... </span>    license=<span class="hljs-string">&quot;mit&quot;</span>,
<span class="hljs-meta">... </span>    sdk=<span class="hljs-string">&quot;gradio&quot;</span>,
<span class="hljs-meta">... </span>    duplicated_from=<span class="hljs-string">&quot;multimodalart/dreambooth-training&quot;</span>
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>card_data.to_dict()
{<span class="hljs-string">&#x27;title&#x27;</span>: <span class="hljs-string">&#x27;Dreambooth Training&#x27;</span>, <span class="hljs-string">&#x27;sdk&#x27;</span>: <span class="hljs-string">&#x27;gradio&#x27;</span>, <span class="hljs-string">&#x27;license&#x27;</span>: <span class="hljs-string">&#x27;mit&#x27;</span>, <span class="hljs-string">&#x27;duplicated_from&#x27;</span>: <span class="hljs-string">&#x27;multimodalart/dreambooth-training&#x27;</span>}`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function qn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub.repocard_data <span class="hljs-keyword">import</span> model_index_to_eval_results
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Define a minimal model index</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>model_index = [
<span class="hljs-meta">... </span>    {
<span class="hljs-meta">... </span>        <span class="hljs-string">&quot;name&quot;</span>: <span class="hljs-string">&quot;my-cool-model&quot;</span>,
<span class="hljs-meta">... </span>        <span class="hljs-string">&quot;results&quot;</span>: [
<span class="hljs-meta">... </span>            {
<span class="hljs-meta">... </span>                <span class="hljs-string">&quot;task&quot;</span>: {
<span class="hljs-meta">... </span>                    <span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;image-classification&quot;</span>
<span class="hljs-meta">... </span>                },
<span class="hljs-meta">... </span>                <span class="hljs-string">&quot;dataset&quot;</span>: {
<span class="hljs-meta">... </span>                    <span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;beans&quot;</span>,
<span class="hljs-meta">... </span>                    <span class="hljs-string">&quot;name&quot;</span>: <span class="hljs-string">&quot;Beans&quot;</span>
<span class="hljs-meta">... </span>                },
<span class="hljs-meta">... </span>                <span class="hljs-string">&quot;metrics&quot;</span>: [
<span class="hljs-meta">... </span>                    {
<span class="hljs-meta">... </span>                        <span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;accuracy&quot;</span>,
<span class="hljs-meta">... </span>                        <span class="hljs-string">&quot;value&quot;</span>: <span class="hljs-number">0.9</span>
<span class="hljs-meta">... </span>                    }
<span class="hljs-meta">... </span>                ]
<span class="hljs-meta">... </span>            }
<span class="hljs-meta">... </span>        ]
<span class="hljs-meta">... </span>    }
<span class="hljs-meta">... </span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>model_name, eval_results = model_index_to_eval_results(model_index)
<span class="hljs-meta">&gt;&gt;&gt; </span>model_name
<span class="hljs-string">&#x27;my-cool-model&#x27;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>eval_results[<span class="hljs-number">0</span>].task_type
<span class="hljs-string">&#x27;image-classification&#x27;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>eval_results[<span class="hljs-number">0</span>].metric_type
<span class="hljs-string">&#x27;accuracy&#x27;</span>
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function zn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub.repocard_data <span class="hljs-keyword">import</span> eval_results_to_model_index, EvalResult
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Define minimal eval_results</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>eval_results = [
<span class="hljs-meta">... </span>    EvalResult(
<span class="hljs-meta">... </span>        task_type=<span class="hljs-string">&quot;image-classification&quot;</span>,  <span class="hljs-comment"># Required</span>
<span class="hljs-meta">... </span>        dataset_type=<span class="hljs-string">&quot;beans&quot;</span>,  <span class="hljs-comment"># Required</span>
<span class="hljs-meta">... </span>        dataset_name=<span class="hljs-string">&quot;Beans&quot;</span>,  <span class="hljs-comment"># Required</span>
<span class="hljs-meta">... </span>        metric_type=<span class="hljs-string">&quot;accuracy&quot;</span>,  <span class="hljs-comment"># Required</span>
<span class="hljs-meta">... </span>        metric_value=<span class="hljs-number">0.9</span>,  <span class="hljs-comment"># Required</span>
<span class="hljs-meta">... </span>    )
<span class="hljs-meta">... </span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>eval_results_to_model_index(<span class="hljs-string">&quot;my-cool-model&quot;</span>, eval_results)
[{<span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;my-cool-model&#x27;</span>, <span class="hljs-string">&#x27;results&#x27;</span>: [{<span class="hljs-string">&#x27;task&#x27;</span>: {<span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;image-classification&#x27;</span>}, <span class="hljs-string">&#x27;dataset&#x27;</span>: {<span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;Beans&#x27;</span>, <span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;beans&#x27;</span>}, <span class="hljs-string">&#x27;metrics&#x27;</span>: [{<span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;accuracy&#x27;</span>, <span class="hljs-string">&#x27;value&#x27;</span>: <span class="hljs-number">0.9</span>}]}]}]
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function On(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> metadata_eval_result
<span class="hljs-meta">&gt;&gt;&gt; </span>results = metadata_eval_result(
<span class="hljs-meta">... </span>        model_pretty_name=<span class="hljs-string">&quot;RoBERTa fine-tuned on ReactionGIF&quot;</span>,
<span class="hljs-meta">... </span>        task_pretty_name=<span class="hljs-string">&quot;Text Classification&quot;</span>,
<span class="hljs-meta">... </span>        task_id=<span class="hljs-string">&quot;text-classification&quot;</span>,
<span class="hljs-meta">... </span>        metrics_pretty_name=<span class="hljs-string">&quot;Accuracy&quot;</span>,
<span class="hljs-meta">... </span>        metrics_id=<span class="hljs-string">&quot;accuracy&quot;</span>,
<span class="hljs-meta">... </span>        metrics_value=<span class="hljs-number">0.2662102282047272</span>,
<span class="hljs-meta">... </span>        dataset_pretty_name=<span class="hljs-string">&quot;ReactionJPEG&quot;</span>,
<span class="hljs-meta">... </span>        dataset_id=<span class="hljs-string">&quot;julien-c/reactionjpeg&quot;</span>,
<span class="hljs-meta">... </span>        dataset_config=<span class="hljs-string">&quot;default&quot;</span>,
<span class="hljs-meta">... </span>        dataset_split=<span class="hljs-string">&quot;test&quot;</span>,
<span class="hljs-meta">... </span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>results == {
<span class="hljs-meta">... </span>    <span class="hljs-string">&#x27;model-index&#x27;</span>: [
<span class="hljs-meta">... </span>        {
<span class="hljs-meta">... </span>            <span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;RoBERTa fine-tuned on ReactionGIF&#x27;</span>,
<span class="hljs-meta">... </span>            <span class="hljs-string">&#x27;results&#x27;</span>: [
<span class="hljs-meta">... </span>                {
<span class="hljs-meta">... </span>                    <span class="hljs-string">&#x27;task&#x27;</span>: {
<span class="hljs-meta">... </span>                        <span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;text-classification&#x27;</span>,
<span class="hljs-meta">... </span>                        <span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;Text Classification&#x27;</span>
<span class="hljs-meta">... </span>                    },
<span class="hljs-meta">... </span>                    <span class="hljs-string">&#x27;dataset&#x27;</span>: {
<span class="hljs-meta">... </span>                        <span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;ReactionJPEG&#x27;</span>,
<span class="hljs-meta">... </span>                        <span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;julien-c/reactionjpeg&#x27;</span>,
<span class="hljs-meta">... </span>                        <span class="hljs-string">&#x27;config&#x27;</span>: <span class="hljs-string">&#x27;default&#x27;</span>,
<span class="hljs-meta">... </span>                        <span class="hljs-string">&#x27;split&#x27;</span>: <span class="hljs-string">&#x27;test&#x27;</span>
<span class="hljs-meta">... </span>                    },
<span class="hljs-meta">... </span>                    <span class="hljs-string">&#x27;metrics&#x27;</span>: [
<span class="hljs-meta">... </span>                        {
<span class="hljs-meta">... </span>                            <span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;accuracy&#x27;</span>,
<span class="hljs-meta">... </span>                            <span class="hljs-string">&#x27;value&#x27;</span>: <span class="hljs-number">0.2662102282047272</span>,
<span class="hljs-meta">... </span>                            <span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;Accuracy&#x27;</span>,
<span class="hljs-meta">... </span>                            <span class="hljs-string">&#x27;verified&#x27;</span>: <span class="hljs-literal">False</span>
<span class="hljs-meta">... </span>                        }
<span class="hljs-meta">... </span>                    ]
<span class="hljs-meta">... </span>                }
<span class="hljs-meta">... </span>            ]
<span class="hljs-meta">... </span>        }
<span class="hljs-meta">... </span>    ]
<span class="hljs-meta">... </span>}
<span class="hljs-literal">True</span>
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Pn(x){let n,y="Example:",j,s,_;return s=new X({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> metadata_update
<span class="hljs-meta">&gt;&gt;&gt; </span>metadata = {<span class="hljs-string">&#x27;model-index&#x27;</span>: [{<span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;RoBERTa fine-tuned on ReactionGIF&#x27;</span>,
<span class="hljs-meta">... </span>            <span class="hljs-string">&#x27;results&#x27;</span>: [{<span class="hljs-string">&#x27;dataset&#x27;</span>: {<span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;ReactionGIF&#x27;</span>,
<span class="hljs-meta">... </span>                                     <span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;julien-c/reactiongif&#x27;</span>},
<span class="hljs-meta">... </span>                          <span class="hljs-string">&#x27;metrics&#x27;</span>: [{<span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;Recall&#x27;</span>,
<span class="hljs-meta">... </span>                                       <span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;recall&#x27;</span>,
<span class="hljs-meta">... </span>                                       <span class="hljs-string">&#x27;value&#x27;</span>: <span class="hljs-number">0.7762102282047272</span>}],
<span class="hljs-meta">... </span>                         <span class="hljs-string">&#x27;task&#x27;</span>: {<span class="hljs-string">&#x27;name&#x27;</span>: <span class="hljs-string">&#x27;Text Classification&#x27;</span>,
<span class="hljs-meta">... </span>                                  <span class="hljs-string">&#x27;type&#x27;</span>: <span class="hljs-string">&#x27;text-classification&#x27;</span>}}]}]}
<span class="hljs-meta">&gt;&gt;&gt; </span>url = metadata_update(<span class="hljs-string">&quot;hf-internal-testing/reactiongif-roberta-card&quot;</span>, metadata)
`,wrap:!1}}),{c(){n=d("p"),n.textContent=y,j=o(),g(s.$$.fragment)},l(a){n=p(a,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=y),j=r(a),m(s.$$.fragment,a)},m(a,b){i(a,n,b),i(a,j,b),h(s,a,b),_=!0},p:E,i(a){_||(u(s.$$.fragment,a),_=!0)},o(a){M(s.$$.fragment,a),_=!1},d(a){a&&(t(n),t(j)),f(s,a)}}}function Kn(x){let n,y,j,s,_,a,b,qs=`huggingface_hub 라이브러리는 모델/데이터 세트 카드를 생성, 공유 및 업데이트하기 위한 Python 인터페이스를 제공합니다.
Hub의 모델 카드가 무엇이며 내부적으로 어떻게 작동하는지 더 깊이 있게 알아보려면 <a href="https://huggingface.co/docs/hub/models-cards" rel="nofollow">전용 문서 페이지</a>를 방문하세요. 또한 이러한 유틸리티를 자신의 프로젝트에서 어떻게 사용할 수 있는지 감을 잡기 위해 <a href="../how-to-model-cards">모델 카드 가이드</a>를 확인할 수 있습니다.`,ct,Te,it,ve,zs='<code>RepoCard</code> 객체는 <a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.ModelCard">ModelCard</a>, <a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.DatasetCard">DatasetCard</a> 및 <code>SpaceCard</code>의 상위 클래스입니다.',dt,v,Ae,Ht,N,$e,Lt,Ta,Os=`Initialize a RepoCard from string content. The content should be a
Markdown file with a YAML block at the beginning and a Markdown body.`,qt,se,zt,ne,Ot,V,Ie,Pt,va,Ps="Initialize a RepoCard from a template. By default, it uses the default template.",Kt,Aa,Ks="Templates are Jinja2 templates that can be customized by passing keyword arguments.",es,H,De,as,$a,en="Initialize a RepoCard from a Hugging Face Hub repo’s README.md or a local filepath.",ts,le,ss,oe,ke,ns,Ia,an="Push a RepoCard to a Hugging Face Hub repo.",ls,L,Re,os,Da,tn="Save a RepoCard to a file.",rs,re,cs,q,Ee,is,ka,sn=`Validates card against Hugging Face Hub’s card validation logic.
Using this function requires access to the internet, so it is only called
internally by <a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.RepoCard.push_to_hub">huggingface_hub.repocard.RepoCard.push_to_hub()</a>.`,ds,ce,pt,Ne,gt,Ze,nn='<a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.CardData">CardData</a> 객체는 <a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.ModelCardData">ModelCardData</a>와 <a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.DatasetCardData">DatasetCardData</a>의 상위 클래스입니다.',mt,T,We,ps,Ra,ln="Structure containing metadata from a RepoCard.",gs,Ea,on='<a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.CardData">CardData</a> is the parent class of <a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.ModelCardData">ModelCardData</a> and <a href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.DatasetCardData">DatasetCardData</a>.',ms,Na,rn=`Metadata can be exported as a dictionary or YAML. Export can be customized to alter the representation of the data
(example: flatten evaluation results). <code>CardData</code> behaves as a dictionary (can get, pop, set values) but do not
inherit from <code>dict</code> to allow this export step.`,hs,ie,Ge,us,Za,cn="Get value for a given metadata key.",Ms,de,Ye,fs,Wa,dn="Pop value for a given metadata key.",_s,pe,Se,js,Ga,pn="Converts CardData to a dict.",ys,ge,Be,bs,Ya,gn="Dumps CardData to a YAML block for inclusion in a README.md file.",ht,Qe,ut,Fe,Mt,z,Xe,Cs,Z,Ve,xs,Sa,mn=`Initialize a ModelCard from a template. By default, it uses the default template, which can be found here:
<a href="https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md" rel="nofollow">https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md</a>`,Us,Ba,hn="Templates are Jinja2 templates that can be customized by passing keyword arguments.",Js,me,ft,He,_t,G,Le,ws,Qa,un="Model Card Metadata that is used by Hugging Face Hub when included at the top of your README.md",Ts,he,jt,qe,yt,ze,Mn="ML 커뮤니티에서는 데이터 세트 카드를 데이터 카드라고도 합니다.",bt,Oe,Ct,O,Pe,vs,W,Ke,As,Fa,fn=`Initialize a DatasetCard from a template. By default, it uses the default template, which can be found here:
<a href="https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md" rel="nofollow">https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md</a>`,$s,Xa,_n="Templates are Jinja2 templates that can be customized by passing keyword arguments.",Is,ue,xt,ea,Ut,P,aa,Ds,Va,jn="Dataset Card Metadata that is used by Hugging Face Hub when included at the top of your README.md",Jt,ta,wt,sa,Tt,na,la,vt,oa,At,D,ra,ks,Ha,yn="Space Card Metadata that is used by Hugging Face Hub when included at the top of your README.md",Rs,La,bn='To get an exhaustive reference of Spaces configuration, please visit <a href="https://huggingface.co/docs/hub/spaces-config-reference#spaces-configuration-reference" rel="nofollow">https://huggingface.co/docs/hub/spaces-config-reference#spaces-configuration-reference</a>.',Es,Me,$t,ca,It,ia,Dt,k,da,Ns,qa,Cn="Flattened representation of individual evaluation results found in model-index of Model Cards.",Zs,za,xn='For more information on the model-index spec, see <a href="https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1" rel="nofollow">https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1</a>.',Ws,fe,pa,Gs,Oa,Un=`Return True if <code>self</code> and <code>other</code> describe exactly the same metric but with a
different value.`,kt,ga,Rt,R,ma,Ys,Pa,Jn="Takes in a model index and returns the model name and a list of <code>huggingface_hub.EvalResult</code> objects.",Ss,Ka,wn=`A detailed spec of the model index can be found here:
<a href="https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1" rel="nofollow">https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1</a>`,Bs,_e,Et,ha,Nt,Y,ua,Qs,et,Tn=`Takes in given model name and list of <code>huggingface_hub.EvalResult</code> and returns a
valid model-index that will be compatible with the format expected by the
Hugging Face Hub.`,Fs,je,Zt,Ma,Wt,S,fa,Xs,at,vn="Creates a metadata dict with the result from a model evaluated on a dataset.",Vs,ye,Gt,_a,Yt,B,ja,Hs,tt,An=`Updates the metadata in the README.md of a repository on the Hugging Face Hub.
If the README.md file doesn’t exist yet, a new one is created with metadata and an
the default ModelCard or DatasetCard template. For <code>space</code> repo, an error is thrown
as a Space cannot exist without a <code>README.md</code> file.`,Ls,be,St,ya,Bt,rt,Qt;return _=new $({props:{title:"리포지토리 카드",local:"repository-cards",headingTag:"h1"}}),Te=new $({props:{title:"리포지토리 카드",local:"huggingface_hub.RepoCard ][ huggingface_hub.RepoCard",headingTag:"h2"}}),Ae=new w({props:{name:"class huggingface_hub.RepoCard",anchor:"huggingface_hub.RepoCard",parameters:[{name:"content",val:": str"},{name:"ignore_metadata_errors",val:": bool = False"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L37"}}),$e=new w({props:{name:"__init__",anchor:"huggingface_hub.RepoCard.__init__",parameters:[{name:"content",val:": str"},{name:"ignore_metadata_errors",val:": bool = False"}],parametersDescription:[{anchor:"huggingface_hub.RepoCard.__init__.content",description:"<strong>content</strong> (<code>str</code>) &#x2014; The content of the Markdown file.",name:"content"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L42"}}),se=new F({props:{anchor:"huggingface_hub.RepoCard.__init__.example",$$slots:{default:[Yn]},$$scope:{ctx:x}}}),ne=new In({props:{$$slots:{default:[Sn]},$$scope:{ctx:x}}}),Ie=new w({props:{name:"from_template",anchor:"huggingface_hub.RepoCard.from_template",parameters:[{name:"card_data",val:": CardData"},{name:"template_path",val:": Optional = None"},{name:"template_str",val:": Optional = None"},{name:"**template_kwargs",val:""}],parametersDescription:[{anchor:"huggingface_hub.RepoCard.from_template.card_data",description:`<strong>card_data</strong> (<code>huggingface_hub.CardData</code>) &#x2014;
A huggingface_hub.CardData instance containing the metadata you want to include in the YAML
header of the repo card on the Hugging Face Hub.`,name:"card_data"},{anchor:"huggingface_hub.RepoCard.from_template.template_path",description:`<strong>template_path</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A path to a markdown file with optional Jinja template variables that can be filled
in with <code>template_kwargs</code>. Defaults to the default template.`,name:"template_path"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L292",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>A RepoCard instance with the specified card data and content from the
template.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><a
  href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.RepoCard"
>huggingface_hub.repocard.RepoCard</a></p>
`}}),De=new w({props:{name:"load",anchor:"huggingface_hub.RepoCard.load",parameters:[{name:"repo_id_or_path",val:": Union"},{name:"repo_type",val:": Optional = None"},{name:"token",val:": Optional = None"},{name:"ignore_metadata_errors",val:": bool = False"}],parametersDescription:[{anchor:"huggingface_hub.RepoCard.load.repo_id_or_path",description:`<strong>repo_id_or_path</strong> (<code>Union[str, Path]</code>) &#x2014;
The repo ID associated with a Hugging Face Hub repo or a local filepath.`,name:"repo_id_or_path"},{anchor:"huggingface_hub.RepoCard.load.repo_type",description:`<strong>repo_type</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The type of Hugging Face repo to push to. Defaults to None, which will use use &#x201C;model&#x201D;. Other options
are &#x201C;dataset&#x201D; and &#x201C;space&#x201D;. Not used when loading from a local filepath. If this is called from a child
class, the default value will be the child class&#x2019;s <code>repo_type</code>.`,name:"repo_type"},{anchor:"huggingface_hub.RepoCard.load.token",description:`<strong>token</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Authentication token, obtained with <code>huggingface_hub.HfApi.login</code> method. Will default to the stored token.`,name:"token"},{anchor:"huggingface_hub.RepoCard.load.ignore_metadata_errors",description:`<strong>ignore_metadata_errors</strong> (<code>str</code>) &#x2014;
If True, errors while parsing the metadata section will be ignored. Some information might be lost during
the process. Use it at your own risk.`,name:"ignore_metadata_errors"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L136",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>The RepoCard (or subclass) initialized from the repo’s
README.md file or filepath.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><a
  href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.RepoCard"
>huggingface_hub.repocard.RepoCard</a></p>
`}}),le=new F({props:{anchor:"huggingface_hub.RepoCard.load.example",$$slots:{default:[Bn]},$$scope:{ctx:x}}}),ke=new w({props:{name:"push_to_hub",anchor:"huggingface_hub.RepoCard.push_to_hub",parameters:[{name:"repo_id",val:": str"},{name:"token",val:": Optional = None"},{name:"repo_type",val:": Optional = None"},{name:"commit_message",val:": Optional = None"},{name:"commit_description",val:": Optional = None"},{name:"revision",val:": Optional = None"},{name:"create_pr",val:": Optional = None"},{name:"parent_commit",val:": Optional = None"}],parametersDescription:[{anchor:"huggingface_hub.RepoCard.push_to_hub.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) &#x2014;
The repo ID of the Hugging Face Hub repo to push to. Example: &#x201C;nateraw/food&#x201D;.`,name:"repo_id"},{anchor:"huggingface_hub.RepoCard.push_to_hub.token",description:`<strong>token</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Authentication token, obtained with <code>huggingface_hub.HfApi.login</code> method. Will default to
the stored token.`,name:"token"},{anchor:"huggingface_hub.RepoCard.push_to_hub.repo_type",description:`<strong>repo_type</strong> (<code>str</code>, <em>optional</em>, defaults to &#x201C;model&#x201D;) &#x2014;
The type of Hugging Face repo to push to. Options are &#x201C;model&#x201D;, &#x201C;dataset&#x201D;, and &#x201C;space&#x201D;. If this
function is called by a child class, it will default to the child class&#x2019;s <code>repo_type</code>.`,name:"repo_type"},{anchor:"huggingface_hub.RepoCard.push_to_hub.commit_message",description:`<strong>commit_message</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The summary / title / first line of the generated commit.`,name:"commit_message"},{anchor:"huggingface_hub.RepoCard.push_to_hub.commit_description",description:`<strong>commit_description</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The description of the generated commit.`,name:"commit_description"},{anchor:"huggingface_hub.RepoCard.push_to_hub.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The git revision to commit from. Defaults to the head of the <code>&quot;main&quot;</code> branch.`,name:"revision"},{anchor:"huggingface_hub.RepoCard.push_to_hub.create_pr",description:`<strong>create_pr</strong> (<code>bool</code>, <em>optional</em>) &#x2014;
Whether or not to create a Pull Request with this commit. Defaults to <code>False</code>.`,name:"create_pr"},{anchor:"huggingface_hub.RepoCard.push_to_hub.parent_commit",description:`<strong>parent_commit</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
If specified and <code>create_pr</code> is <code>False</code>, the commit will fail if <code>revision</code> does not point to <code>parent_commit</code>.
If specified and <code>create_pr</code> is <code>True</code>, the pull request will be created from <code>parent_commit</code>.
Specifying <code>parent_commit</code> ensures the repo has not changed before committing the changes, and can be
especially useful if the repo is updated / committed to concurrently.`,name:"parent_commit"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L229",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>URL of the commit which updated the card metadata.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>str</code></p>
`}}),Re=new w({props:{name:"save",anchor:"huggingface_hub.RepoCard.save",parameters:[{name:"filepath",val:": Union"}],parametersDescription:[{anchor:"huggingface_hub.RepoCard.save.filepath",description:"<strong>filepath</strong> (<code>Union[Path, str]</code>) &#x2014; Filepath to the markdown file to save.",name:"filepath"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L116"}}),re=new F({props:{anchor:"huggingface_hub.RepoCard.save.example",$$slots:{default:[Qn]},$$scope:{ctx:x}}}),Ee=new w({props:{name:"validate",anchor:"huggingface_hub.RepoCard.validate",parameters:[{name:"repo_type",val:": Optional = None"}],parametersDescription:[{anchor:"huggingface_hub.RepoCard.validate.repo_type",description:`<strong>repo_type</strong> (<code>str</code>, <em>optional</em>, defaults to &#x201C;model&#x201D;) &#x2014;
The type of Hugging Face repo to push to. Options are &#x201C;model&#x201D;, &#x201C;dataset&#x201D;, and &#x201C;space&#x201D;.
If this function is called from a child class, the default will be the child class&#x2019;s <code>repo_type</code>.`,name:"repo_type"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L190"}}),ce=new In({props:{$$slots:{default:[Fn]},$$scope:{ctx:x}}}),Ne=new $({props:{title:"카드 데이터",local:"huggingface_hub.CardData ][ huggingface_hub.CardData",headingTag:"h2"}}),We=new w({props:{name:"class huggingface_hub.CardData",anchor:"huggingface_hub.CardData",parameters:[{name:"ignore_metadata_errors",val:": bool = False"},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L164"}}),Ge=new w({props:{name:"get",anchor:"huggingface_hub.CardData.get",parameters:[{name:"key",val:": str"},{name:"default",val:": Any = None"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L216"}}),Ye=new w({props:{name:"pop",anchor:"huggingface_hub.CardData.pop",parameters:[{name:"key",val:": str"},{name:"default",val:": Any = None"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L220"}}),Se=new w({props:{name:"to_dict",anchor:"huggingface_hub.CardData.to_dict",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L178",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>CardData represented as a dictionary ready to be dumped to a YAML
block for inclusion in a README.md file.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>dict</code></p>
`}}),Be=new w({props:{name:"to_yaml",anchor:"huggingface_hub.CardData.to_yaml",parameters:[{name:"line_break",val:" = None"}],parametersDescription:[{anchor:"huggingface_hub.CardData.to_yaml.line_break",description:`<strong>line_break</strong> (str, <em>optional</em>) &#x2014;
The line break to use when dumping to yaml.`,name:"line_break"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L198",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>CardData represented as a YAML block.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>str</code></p>
`}}),Qe=new $({props:{title:"모델 카드",local:"model-cards",headingTag:"h2"}}),Fe=new $({props:{title:"ModelCard",local:"huggingface_hub.ModelCard ][ huggingface_hub.ModelCard",headingTag:"h3"}}),Xe=new w({props:{name:"class huggingface_hub.ModelCard",anchor:"huggingface_hub.ModelCard",parameters:[{name:"content",val:": str"},{name:"ignore_metadata_errors",val:": bool = False"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L336"}}),Ve=new w({props:{name:"from_template",anchor:"huggingface_hub.ModelCard.from_template",parameters:[{name:"card_data",val:": ModelCardData"},{name:"template_path",val:": Optional = None"},{name:"template_str",val:": Optional = None"},{name:"**template_kwargs",val:""}],parametersDescription:[{anchor:"huggingface_hub.ModelCard.from_template.card_data",description:`<strong>card_data</strong> (<code>huggingface_hub.ModelCardData</code>) &#x2014;
A huggingface_hub.ModelCardData instance containing the metadata you want to include in the YAML
header of the model card on the Hugging Face Hub.`,name:"card_data"},{anchor:"huggingface_hub.ModelCard.from_template.template_path",description:`<strong>template_path</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A path to a markdown file with optional Jinja template variables that can be filled
in with <code>template_kwargs</code>. Defaults to the default template.`,name:"template_path"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L341",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>A ModelCard instance with the specified card data and content from the
template.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><a
  href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.ModelCard"
>huggingface_hub.ModelCard</a></p>
`}}),me=new F({props:{anchor:"huggingface_hub.ModelCard.from_template.example",$$slots:{default:[Xn]},$$scope:{ctx:x}}}),He=new $({props:{title:"ModelCardData",local:"huggingface_hub.ModelCardData ][ huggingface_hub.ModelCardData",headingTag:"h3"}}),Le=new w({props:{name:"class huggingface_hub.ModelCardData",anchor:"huggingface_hub.ModelCardData",parameters:[{name:"base_model",val:": Union = None"},{name:"datasets",val:": Optional = None"},{name:"eval_results",val:": Optional = None"},{name:"language",val:": Union = None"},{name:"library_name",val:": Optional = None"},{name:"license",val:": Optional = None"},{name:"license_name",val:": Optional = None"},{name:"license_link",val:": Optional = None"},{name:"metrics",val:": Optional = None"},{name:"model_name",val:": Optional = None"},{name:"pipeline_tag",val:": Optional = None"},{name:"tags",val:": Optional = None"},{name:"ignore_metadata_errors",val:": bool = False"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"huggingface_hub.ModelCardData.base_model",description:`<strong>base_model</strong> (<code>str</code> or <code>List[str]</code>, <em>optional</em>) &#x2014;
The identifier of the base model from which the model derives. This is applicable for example if your model is a
fine-tune or adapter of an existing model. The value must be the ID of a model on the Hub (or a list of IDs
if your model derives from multiple models). Defaults to None.`,name:"base_model"},{anchor:"huggingface_hub.ModelCardData.datasets",description:`<strong>datasets</strong> (<code>List[str]</code>, <em>optional</em>) &#x2014;
List of datasets that were used to train this model. Should be a dataset ID
found on <a href="https://hf.co/datasets" rel="nofollow">https://hf.co/datasets</a>. Defaults to None.`,name:"datasets"},{anchor:"huggingface_hub.ModelCardData.eval_results",description:`<strong>eval_results</strong> (<code>Union[List[EvalResult], EvalResult]</code>, <em>optional</em>) &#x2014;
List of <code>huggingface_hub.EvalResult</code> that define evaluation results of the model. If provided,
<code>model_name</code> is used to as a name on PapersWithCode&#x2019;s leaderboards. Defaults to <code>None</code>.`,name:"eval_results"},{anchor:"huggingface_hub.ModelCardData.language",description:`<strong>language</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
Language of model&#x2019;s training data or metadata. It must be an ISO 639-1, 639-2 or
639-3 code (two/three letters), or a special value like &#x201C;code&#x201D;, &#x201C;multilingual&#x201D;. Defaults to <code>None</code>.`,name:"language"},{anchor:"huggingface_hub.ModelCardData.library_name",description:`<strong>library_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Name of library used by this model. Example: keras or any library from
<a href="https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/model-libraries.ts" rel="nofollow">https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/model-libraries.ts</a>.
Defaults to None.`,name:"library_name"},{anchor:"huggingface_hub.ModelCardData.license",description:`<strong>license</strong> (<code>str</code>, <em>optional</em>) &#x2014;
License of this model. Example: apache-2.0 or any license from
<a href="https://huggingface.co/docs/hub/repositories-licenses" rel="nofollow">https://huggingface.co/docs/hub/repositories-licenses</a>. Defaults to None.`,name:"license"},{anchor:"huggingface_hub.ModelCardData.license_name",description:`<strong>license_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Name of the license of this model. Defaults to None. To be used in conjunction with <code>license_link</code>.
Common licenses (Apache-2.0, MIT, CC-BY-SA-4.0) do not need a name. In that case, use <code>license</code> instead.`,name:"license_name"},{anchor:"huggingface_hub.ModelCardData.license_link",description:`<strong>license_link</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Link to the license of this model. Defaults to None. To be used in conjunction with <code>license_name</code>.
Common licenses (Apache-2.0, MIT, CC-BY-SA-4.0) do not need a link. In that case, use <code>license</code> instead.`,name:"license_link"},{anchor:"huggingface_hub.ModelCardData.metrics",description:`<strong>metrics</strong> (<code>List[str]</code>, <em>optional</em>) &#x2014;
List of metrics used to evaluate this model. Should be a metric name that can be found
at <a href="https://hf.co/metrics" rel="nofollow">https://hf.co/metrics</a>. Example: &#x2018;accuracy&#x2019;. Defaults to None.`,name:"metrics"},{anchor:"huggingface_hub.ModelCardData.model_name",description:`<strong>model_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A name for this model. It is used along with
<code>eval_results</code> to construct the <code>model-index</code> within the card&#x2019;s metadata. The name
you supply here is what will be used on PapersWithCode&#x2019;s leaderboards. If None is provided
then the repo name is used as a default. Defaults to None.`,name:"model_name"},{anchor:"huggingface_hub.ModelCardData.tags",description:`<strong>tags</strong> (<code>List[str]</code>, <em>optional</em>) &#x2014;
List of tags to add to your model that can be used when filtering on the Hugging
Face Hub. Defaults to None.`,name:"tags"},{anchor:"huggingface_hub.ModelCardData.ignore_metadata_errors",description:`<strong>ignore_metadata_errors</strong> (<code>str</code>) &#x2014;
If True, errors while parsing the metadata section will be ignored. Some information might be lost during
the process. Use it at your own risk.`,name:"ignore_metadata_errors"},{anchor:"huggingface_hub.ModelCardData.kwargs",description:`<strong>kwargs</strong> (<code>dict</code>, <em>optional</em>) &#x2014;
Additional metadata that will be added to the model card. Defaults to None.`,name:"kwargs"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L241"}}),he=new F({props:{anchor:"huggingface_hub.ModelCardData.example",$$slots:{default:[Vn]},$$scope:{ctx:x}}}),qe=new $({props:{title:"데이터 세트 카드",local:"cards#dataset-cards",headingTag:"h2"}}),Oe=new $({props:{title:"DatasetCard",local:"huggingface_hub.DatasetCard ][ huggingface_hub.DatasetCard",headingTag:"h3"}}),Pe=new w({props:{name:"class huggingface_hub.DatasetCard",anchor:"huggingface_hub.DatasetCard",parameters:[{name:"content",val:": str"},{name:"ignore_metadata_errors",val:": bool = False"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L417"}}),Ke=new w({props:{name:"from_template",anchor:"huggingface_hub.DatasetCard.from_template",parameters:[{name:"card_data",val:": DatasetCardData"},{name:"template_path",val:": Optional = None"},{name:"template_str",val:": Optional = None"},{name:"**template_kwargs",val:""}],parametersDescription:[{anchor:"huggingface_hub.DatasetCard.from_template.card_data",description:`<strong>card_data</strong> (<code>huggingface_hub.DatasetCardData</code>) &#x2014;
A huggingface_hub.DatasetCardData instance containing the metadata you want to include in the YAML
header of the dataset card on the Hugging Face Hub.`,name:"card_data"},{anchor:"huggingface_hub.DatasetCard.from_template.template_path",description:`<strong>template_path</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A path to a markdown file with optional Jinja template variables that can be filled
in with <code>template_kwargs</code>. Defaults to the default template.`,name:"template_path"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L422",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>A DatasetCard instance with the specified card data and content from the
template.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><a
  href="/docs/huggingface_hub/pr_2402/ko/package_reference/cards#huggingface_hub.DatasetCard"
>huggingface_hub.DatasetCard</a></p>
`}}),ue=new F({props:{anchor:"huggingface_hub.DatasetCard.from_template.example",$$slots:{default:[Hn]},$$scope:{ctx:x}}}),ea=new $({props:{title:"DatasetCardData",local:"huggingface_hub.DatasetCardData ][ huggingface_hub.DatasetCardData",headingTag:"h3"}}),aa=new w({props:{name:"class huggingface_hub.DatasetCardData",anchor:"huggingface_hub.DatasetCardData",parameters:[{name:"language",val:": Union = None"},{name:"license",val:": Union = None"},{name:"annotations_creators",val:": Union = None"},{name:"language_creators",val:": Union = None"},{name:"multilinguality",val:": Union = None"},{name:"size_categories",val:": Union = None"},{name:"source_datasets",val:": Optional = None"},{name:"task_categories",val:": Union = None"},{name:"task_ids",val:": Union = None"},{name:"paperswithcode_id",val:": Optional = None"},{name:"pretty_name",val:": Optional = None"},{name:"train_eval_index",val:": Optional = None"},{name:"config_names",val:": Union = None"},{name:"ignore_metadata_errors",val:": bool = False"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"huggingface_hub.DatasetCardData.language",description:`<strong>language</strong> (<code>List[str]</code>, <em>optional</em>) &#x2014;
Language of dataset&#x2019;s data or metadata. It must be an ISO 639-1, 639-2 or
639-3 code (two/three letters), or a special value like &#x201C;code&#x201D;, &#x201C;multilingual&#x201D;.`,name:"language"},{anchor:"huggingface_hub.DatasetCardData.license",description:`<strong>license</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
License(s) of this dataset. Example: apache-2.0 or any license from
<a href="https://huggingface.co/docs/hub/repositories-licenses" rel="nofollow">https://huggingface.co/docs/hub/repositories-licenses</a>.`,name:"license"},{anchor:"huggingface_hub.DatasetCardData.annotations_creators",description:`<strong>annotations_creators</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
How the annotations for the dataset were created.
Options are: &#x2018;found&#x2019;, &#x2018;crowdsourced&#x2019;, &#x2018;expert-generated&#x2019;, &#x2018;machine-generated&#x2019;, &#x2018;no-annotation&#x2019;, &#x2018;other&#x2019;.`,name:"annotations_creators"},{anchor:"huggingface_hub.DatasetCardData.language_creators",description:`<strong>language_creators</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
How the text-based data in the dataset was created.
Options are: &#x2018;found&#x2019;, &#x2018;crowdsourced&#x2019;, &#x2018;expert-generated&#x2019;, &#x2018;machine-generated&#x2019;, &#x2018;other&#x2019;`,name:"language_creators"},{anchor:"huggingface_hub.DatasetCardData.multilinguality",description:`<strong>multilinguality</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
Whether the dataset is multilingual.
Options are: &#x2018;monolingual&#x2019;, &#x2018;multilingual&#x2019;, &#x2018;translation&#x2019;, &#x2018;other&#x2019;.`,name:"multilinguality"},{anchor:"huggingface_hub.DatasetCardData.size_categories",description:`<strong>size_categories</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
The number of examples in the dataset. Options are: &#x2018;n&lt;1K&#x2019;, &#x2018;1K<n<10k’, ‘10k<n<100k’, ‘100k<n<1m’, ‘1m<n<10m’, ‘10m<n<100m’, ‘100m<n<1b’, ‘1b<n<10b’, ‘10b<n<100b’, ‘100b<n<1t’, ‘n>1T&#x2019;, and &#x2018;other&#x2019;.</n<10k’,>`,name:"size_categories"},{anchor:"huggingface_hub.DatasetCardData.source_datasets",description:`<strong>source_datasets</strong> (<code>List[str]]</code>, <em>optional</em>) &#x2014;
Indicates whether the dataset is an original dataset or extended from another existing dataset.
Options are: &#x2018;original&#x2019; and &#x2018;extended&#x2019;.`,name:"source_datasets"},{anchor:"huggingface_hub.DatasetCardData.task_categories",description:`<strong>task_categories</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
What categories of task does the dataset support?`,name:"task_categories"},{anchor:"huggingface_hub.DatasetCardData.task_ids",description:`<strong>task_ids</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
What specific tasks does the dataset support?`,name:"task_ids"},{anchor:"huggingface_hub.DatasetCardData.paperswithcode_id",description:`<strong>paperswithcode_id</strong> (<code>str</code>, <em>optional</em>) &#x2014;
ID of the dataset on PapersWithCode.`,name:"paperswithcode_id"},{anchor:"huggingface_hub.DatasetCardData.pretty_name",description:`<strong>pretty_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A more human-readable name for the dataset. (ex. &#x201C;Cats vs. Dogs&#x201D;)`,name:"pretty_name"},{anchor:"huggingface_hub.DatasetCardData.train_eval_index",description:`<strong>train_eval_index</strong> (<code>Dict</code>, <em>optional</em>) &#x2014;
A dictionary that describes the necessary spec for doing evaluation on the Hub.
If not provided, it will be gathered from the &#x2018;train-eval-index&#x2019; key of the kwargs.`,name:"train_eval_index"},{anchor:"huggingface_hub.DatasetCardData.config_names",description:`<strong>config_names</strong> (<code>Union[str, List[str]]</code>, <em>optional</em>) &#x2014;
A list of the available dataset configs for the dataset.`,name:"config_names"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L365"}}),ta=new $({props:{title:"공간 카드",local:"space-cards",headingTag:"h2"}}),sa=new $({props:{title:"SpaceCard",local:"huggingface_hub.SpaceCardData ][ huggingface_hub.SpaceCard",headingTag:"h3"}}),la=new w({props:{name:"class huggingface_hub.SpaceCard",anchor:"huggingface_hub.SpaceCard",parameters:[{name:"content",val:": str"},{name:"ignore_metadata_errors",val:": bool = False"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L482"}}),oa=new $({props:{title:"SpaceCardData",local:"huggingface_hub.SpaceCardData ][ huggingface_hub.SpaceCardData",headingTag:"h3"}}),ra=new w({props:{name:"class huggingface_hub.SpaceCardData",anchor:"huggingface_hub.SpaceCardData",parameters:[{name:"title",val:": Optional = None"},{name:"sdk",val:": Optional = None"},{name:"sdk_version",val:": Optional = None"},{name:"python_version",val:": Optional = None"},{name:"app_file",val:": Optional = None"},{name:"app_port",val:": Optional = None"},{name:"license",val:": Optional = None"},{name:"duplicated_from",val:": Optional = None"},{name:"models",val:": Optional = None"},{name:"datasets",val:": Optional = None"},{name:"tags",val:": Optional = None"},{name:"ignore_metadata_errors",val:": bool = False"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"huggingface_hub.SpaceCardData.title",description:`<strong>title</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Title of the Space.`,name:"title"},{anchor:"huggingface_hub.SpaceCardData.sdk",description:`<strong>sdk</strong> (<code>str</code>, <em>optional</em>) &#x2014;
SDK of the Space (one of <code>gradio</code>, <code>streamlit</code>, <code>docker</code>, or <code>static</code>).`,name:"sdk"},{anchor:"huggingface_hub.SpaceCardData.sdk_version",description:`<strong>sdk_version</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Version of the used SDK (if Gradio/Streamlit sdk).`,name:"sdk_version"},{anchor:"huggingface_hub.SpaceCardData.python_version",description:`<strong>python_version</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Python version used in the Space (if Gradio/Streamlit sdk).`,name:"python_version"},{anchor:"huggingface_hub.SpaceCardData.app_file",description:`<strong>app_file</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Path to your main application file (which contains either gradio or streamlit Python code, or static html code).
Path is relative to the root of the repository.`,name:"app_file"},{anchor:"huggingface_hub.SpaceCardData.app_port",description:`<strong>app_port</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Port on which your application is running. Used only if sdk is <code>docker</code>.`,name:"app_port"},{anchor:"huggingface_hub.SpaceCardData.license",description:`<strong>license</strong> (<code>str</code>, <em>optional</em>) &#x2014;
License of this model. Example: apache-2.0 or any license from
<a href="https://huggingface.co/docs/hub/repositories-licenses" rel="nofollow">https://huggingface.co/docs/hub/repositories-licenses</a>.`,name:"license"},{anchor:"huggingface_hub.SpaceCardData.duplicated_from",description:`<strong>duplicated_from</strong> (<code>str</code>, <em>optional</em>) &#x2014;
ID of the original Space if this is a duplicated Space.`,name:"duplicated_from"},{anchor:"huggingface_hub.SpaceCardData.models",description:`<strong>models</strong> (List<code>str</code>, <em>optional</em>) &#x2014;
List of models related to this Space. Should be a dataset ID found on <a href="https://hf.co/models" rel="nofollow">https://hf.co/models</a>.`,name:"models"},{anchor:"huggingface_hub.SpaceCardData.datasets",description:`<strong>datasets</strong> (<code>List[str]</code>, <em>optional</em>) &#x2014;
List of datasets related to this Space. Should be a dataset ID found on <a href="https://hf.co/datasets" rel="nofollow">https://hf.co/datasets</a>.`,name:"datasets"},{anchor:"huggingface_hub.SpaceCardData.tags",description:`<strong>tags</strong> (<code>List[str]</code>, <em>optional</em>) &#x2014;
List of tags to add to your Space that can be used when filtering on the Hub.`,name:"tags"},{anchor:"huggingface_hub.SpaceCardData.ignore_metadata_errors",description:`<strong>ignore_metadata_errors</strong> (<code>str</code>) &#x2014;
If True, errors while parsing the metadata section will be ignored. Some information might be lost during
the process. Use it at your own risk.`,name:"ignore_metadata_errors"},{anchor:"huggingface_hub.SpaceCardData.kwargs",description:`<strong>kwargs</strong> (<code>dict</code>, <em>optional</em>) &#x2014;
Additional metadata that will be added to the space card.`,name:"kwargs"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L445"}}),Me=new F({props:{anchor:"huggingface_hub.SpaceCardData.example",$$slots:{default:[Ln]},$$scope:{ctx:x}}}),ca=new $({props:{title:"유틸리티",local:"utilities",headingTag:"h2"}}),ia=new $({props:{title:"EvalResult",local:"huggingface_hub.EvalResult ][ huggingface_hub.EvalResult",headingTag:"h3"}}),da=new w({props:{name:"class huggingface_hub.EvalResult",anchor:"huggingface_hub.EvalResult",parameters:[{name:"task_type",val:": str"},{name:"dataset_type",val:": str"},{name:"dataset_name",val:": str"},{name:"metric_type",val:": str"},{name:"metric_value",val:": Any"},{name:"task_name",val:": Optional = None"},{name:"dataset_config",val:": Optional = None"},{name:"dataset_split",val:": Optional = None"},{name:"dataset_revision",val:": Optional = None"},{name:"dataset_args",val:": Optional = None"},{name:"metric_name",val:": Optional = None"},{name:"metric_config",val:": Optional = None"},{name:"metric_args",val:": Optional = None"},{name:"verified",val:": Optional = None"},{name:"verify_token",val:": Optional = None"},{name:"source_name",val:": Optional = None"},{name:"source_url",val:": Optional = None"}],parametersDescription:[{anchor:"huggingface_hub.EvalResult.task_type",description:`<strong>task_type</strong> (<code>str</code>) &#x2014;
The task identifier. Example: &#x201C;image-classification&#x201D;.`,name:"task_type"},{anchor:"huggingface_hub.EvalResult.dataset_type",description:`<strong>dataset_type</strong> (<code>str</code>) &#x2014;
The dataset identifier. Example: &#x201C;common_voice&#x201D;. Use dataset id from <a href="https://hf.co/datasets" rel="nofollow">https://hf.co/datasets</a>.`,name:"dataset_type"},{anchor:"huggingface_hub.EvalResult.dataset_name",description:`<strong>dataset_name</strong> (<code>str</code>) &#x2014;
A pretty name for the dataset. Example: &#x201C;Common Voice (French)&#x201C;.`,name:"dataset_name"},{anchor:"huggingface_hub.EvalResult.metric_type",description:`<strong>metric_type</strong> (<code>str</code>) &#x2014;
The metric identifier. Example: &#x201C;wer&#x201D;. Use metric id from <a href="https://hf.co/metrics" rel="nofollow">https://hf.co/metrics</a>.`,name:"metric_type"},{anchor:"huggingface_hub.EvalResult.metric_value",description:`<strong>metric_value</strong> (<code>Any</code>) &#x2014;
The metric value. Example: 0.9 or &#x201C;20.0 &#xB1; 1.2&#x201D;.`,name:"metric_value"},{anchor:"huggingface_hub.EvalResult.task_name",description:`<strong>task_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A pretty name for the task. Example: &#x201C;Speech Recognition&#x201D;.`,name:"task_name"},{anchor:"huggingface_hub.EvalResult.dataset_config",description:`<strong>dataset_config</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The name of the dataset configuration used in <code>load_dataset()</code>.
Example: fr in <code>load_dataset(&quot;common_voice&quot;, &quot;fr&quot;)</code>. See the <code>datasets</code> docs for more info:
<a href="https://hf.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name" rel="nofollow">https://hf.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name</a>`,name:"dataset_config"},{anchor:"huggingface_hub.EvalResult.dataset_split",description:`<strong>dataset_split</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The split used in <code>load_dataset()</code>. Example: &#x201C;test&#x201D;.`,name:"dataset_split"},{anchor:"huggingface_hub.EvalResult.dataset_revision",description:`<strong>dataset_revision</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The revision (AKA Git Sha) of the dataset used in <code>load_dataset()</code>.
Example: 5503434ddd753f426f4b38109466949a1217c2bb`,name:"dataset_revision"},{anchor:"huggingface_hub.EvalResult.dataset_args",description:`<strong>dataset_args</strong> (<code>Dict[str, Any]</code>, <em>optional</em>) &#x2014;
The arguments passed during <code>Metric.compute()</code>. Example for <code>bleu</code>: <code>{&quot;max_order&quot;: 4}</code>`,name:"dataset_args"},{anchor:"huggingface_hub.EvalResult.metric_name",description:`<strong>metric_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A pretty name for the metric. Example: &#x201C;Test WER&#x201D;.`,name:"metric_name"},{anchor:"huggingface_hub.EvalResult.metric_config",description:`<strong>metric_config</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The name of the metric configuration used in <code>load_metric()</code>.
Example: bleurt-large-512 in <code>load_metric(&quot;bleurt&quot;, &quot;bleurt-large-512&quot;)</code>.
See the <code>datasets</code> docs for more info: <a href="https://huggingface.co/docs/datasets/v2.1.0/en/loading#load-configurations" rel="nofollow">https://huggingface.co/docs/datasets/v2.1.0/en/loading#load-configurations</a>`,name:"metric_config"},{anchor:"huggingface_hub.EvalResult.metric_args",description:`<strong>metric_args</strong> (<code>Dict[str, Any]</code>, <em>optional</em>) &#x2014;
The arguments passed during <code>Metric.compute()</code>. Example for <code>bleu</code>: max_order: 4`,name:"metric_args"},{anchor:"huggingface_hub.EvalResult.verified",description:`<strong>verified</strong> (<code>bool</code>, <em>optional</em>) &#x2014;
Indicates whether the metrics originate from Hugging Face&#x2019;s <a href="https://huggingface.co/spaces/autoevaluate/model-evaluator" rel="nofollow">evaluation service</a> or not. Automatically computed by Hugging Face, do not set.`,name:"verified"},{anchor:"huggingface_hub.EvalResult.verify_token",description:`<strong>verify_token</strong> (<code>str</code>, <em>optional</em>) &#x2014;
A JSON Web Token that is used to verify whether the metrics originate from Hugging Face&#x2019;s <a href="https://huggingface.co/spaces/autoevaluate/model-evaluator" rel="nofollow">evaluation service</a> or not.`,name:"verify_token"},{anchor:"huggingface_hub.EvalResult.source_name",description:`<strong>source_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The name of the source of the evaluation result. Example: &#x201C;Open LLM Leaderboard&#x201D;.`,name:"source_name"},{anchor:"huggingface_hub.EvalResult.source_url",description:`<strong>source_url</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The URL of the source of the evaluation result. Example: &#x201D;<a href="https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard%22" rel="nofollow">https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard&#x201D;</a>.`,name:"source_url"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L12"}}),pa=new w({props:{name:"is_equal_except_value",anchor:"huggingface_hub.EvalResult.is_equal_except_value",parameters:[{name:"other",val:": EvalResult"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L145"}}),ga=new $({props:{title:"model_index_to_eval_results",local:"huggingface_hub.repocard_data.model_index_to_eval_results ][ huggingface_hub.repocard_data.model_index_to_eval_results",headingTag:"h3"}}),ma=new w({props:{name:"huggingface_hub.repocard_data.model_index_to_eval_results",anchor:"huggingface_hub.repocard_data.model_index_to_eval_results",parameters:[{name:"model_index",val:": List"}],parametersDescription:[{anchor:"huggingface_hub.repocard_data.model_index_to_eval_results.model_index",description:`<strong>model_index</strong> (<code>List[Dict[str, Any]]</code>) &#x2014;
A model index data structure, likely coming from a README.md file on the
Hugging Face Hub.`,name:"model_index"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L526",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>The name of the model as found in the model index. This is used as the
identifier for the model on leaderboards like PapersWithCode.
eval_results (<code>List[EvalResult]</code>):
A list of <code>huggingface_hub.EvalResult</code> objects containing the metrics
reported in the provided model_index.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p>model_name (<code>str</code>)</p>
`}}),_e=new F({props:{anchor:"huggingface_hub.repocard_data.model_index_to_eval_results.example",$$slots:{default:[qn]},$$scope:{ctx:x}}}),ha=new $({props:{title:"eval_results_to_model_index",local:"huggingface_hub.repocard_data.eval_results_to_model_index ][ huggingface_hub.repocard_data.eval_results_to_model_index",headingTag:"h3"}}),ua=new w({props:{name:"huggingface_hub.repocard_data.eval_results_to_model_index",anchor:"huggingface_hub.repocard_data.eval_results_to_model_index",parameters:[{name:"model_name",val:": str"},{name:"eval_results",val:": List"}],parametersDescription:[{anchor:"huggingface_hub.repocard_data.eval_results_to_model_index.model_name",description:`<strong>model_name</strong> (<code>str</code>) &#x2014;
Name of the model (ex. &#x201C;my-cool-model&#x201D;). This is used as the identifier
for the model on leaderboards like PapersWithCode.`,name:"model_name"},{anchor:"huggingface_hub.repocard_data.eval_results_to_model_index.eval_results",description:`<strong>eval_results</strong> (<code>List[EvalResult]</code>) &#x2014;
List of <code>huggingface_hub.EvalResult</code> objects containing the metrics to be
reported in the model-index.`,name:"eval_results"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard_data.py#L642",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>The eval_results converted to a model-index.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p>model_index (<code>List[Dict[str, Any]]</code>)</p>
`}}),je=new F({props:{anchor:"huggingface_hub.repocard_data.eval_results_to_model_index.example",$$slots:{default:[zn]},$$scope:{ctx:x}}}),Ma=new $({props:{title:"metadata_eval_result",local:"huggingface_hub.metadata_eval_result ][ huggingface_hub.metadata_eval_result",headingTag:"h3"}}),fa=new w({props:{name:"huggingface_hub.metadata_eval_result",anchor:"huggingface_hub.metadata_eval_result",parameters:[{name:"model_pretty_name",val:": str"},{name:"task_pretty_name",val:": str"},{name:"task_id",val:": str"},{name:"metrics_pretty_name",val:": str"},{name:"metrics_id",val:": str"},{name:"metrics_value",val:": Any"},{name:"dataset_pretty_name",val:": str"},{name:"dataset_id",val:": str"},{name:"metrics_config",val:": Optional = None"},{name:"metrics_verified",val:": bool = False"},{name:"dataset_config",val:": Optional = None"},{name:"dataset_split",val:": Optional = None"},{name:"dataset_revision",val:": Optional = None"},{name:"metrics_verification_token",val:": Optional = None"}],parametersDescription:[{anchor:"huggingface_hub.metadata_eval_result.model_pretty_name",description:`<strong>model_pretty_name</strong> (<code>str</code>) &#x2014;
The name of the model in natural language.`,name:"model_pretty_name"},{anchor:"huggingface_hub.metadata_eval_result.task_pretty_name",description:`<strong>task_pretty_name</strong> (<code>str</code>) &#x2014;
The name of a task in natural language.`,name:"task_pretty_name"},{anchor:"huggingface_hub.metadata_eval_result.task_id",description:`<strong>task_id</strong> (<code>str</code>) &#x2014;
Example: automatic-speech-recognition. A task id.`,name:"task_id"},{anchor:"huggingface_hub.metadata_eval_result.metrics_pretty_name",description:`<strong>metrics_pretty_name</strong> (<code>str</code>) &#x2014;
A name for the metric in natural language. Example: Test WER.`,name:"metrics_pretty_name"},{anchor:"huggingface_hub.metadata_eval_result.metrics_id",description:`<strong>metrics_id</strong> (<code>str</code>) &#x2014;
Example: wer. A metric id from <a href="https://hf.co/metrics" rel="nofollow">https://hf.co/metrics</a>.`,name:"metrics_id"},{anchor:"huggingface_hub.metadata_eval_result.metrics_value",description:`<strong>metrics_value</strong> (<code>Any</code>) &#x2014;
The value from the metric. Example: 20.0 or &#x201C;20.0 &#xB1; 1.2&#x201D;.`,name:"metrics_value"},{anchor:"huggingface_hub.metadata_eval_result.dataset_pretty_name",description:`<strong>dataset_pretty_name</strong> (<code>str</code>) &#x2014;
The name of the dataset in natural language.`,name:"dataset_pretty_name"},{anchor:"huggingface_hub.metadata_eval_result.dataset_id",description:`<strong>dataset_id</strong> (<code>str</code>) &#x2014;
Example: common_voice. A dataset id from <a href="https://hf.co/datasets" rel="nofollow">https://hf.co/datasets</a>.`,name:"dataset_id"},{anchor:"huggingface_hub.metadata_eval_result.metrics_config",description:`<strong>metrics_config</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The name of the metric configuration used in <code>load_metric()</code>.
Example: bleurt-large-512 in <code>load_metric(&quot;bleurt&quot;, &quot;bleurt-large-512&quot;)</code>.`,name:"metrics_config"},{anchor:"huggingface_hub.metadata_eval_result.metrics_verified",description:`<strong>metrics_verified</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) &#x2014;
Indicates whether the metrics originate from Hugging Face&#x2019;s <a href="https://huggingface.co/spaces/autoevaluate/model-evaluator" rel="nofollow">evaluation service</a> or not. Automatically computed by Hugging Face, do not set.`,name:"metrics_verified"},{anchor:"huggingface_hub.metadata_eval_result.dataset_config",description:`<strong>dataset_config</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Example: fr. The name of the dataset configuration used in <code>load_dataset()</code>.`,name:"dataset_config"},{anchor:"huggingface_hub.metadata_eval_result.dataset_split",description:`<strong>dataset_split</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Example: test. The name of the dataset split used in <code>load_dataset()</code>.`,name:"dataset_split"},{anchor:"huggingface_hub.metadata_eval_result.dataset_revision",description:`<strong>dataset_revision</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Example: 5503434ddd753f426f4b38109466949a1217c2bb. The name of the dataset dataset revision
used in <code>load_dataset()</code>.`,name:"dataset_revision"},{anchor:"huggingface_hub.metadata_eval_result.metrics_verification_token",description:`<strong>metrics_verification_token</strong> (<code>bool</code>, <em>optional</em>) &#x2014;
A JSON Web Token that is used to verify whether the metrics originate from Hugging Face&#x2019;s <a href="https://huggingface.co/spaces/autoevaluate/model-evaluator" rel="nofollow">evaluation service</a> or not.`,name:"metrics_verification_token"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L554",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>a metadata dict with the result from a model evaluated on a dataset.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>dict</code></p>
`}}),ye=new F({props:{anchor:"huggingface_hub.metadata_eval_result.example",$$slots:{default:[On]},$$scope:{ctx:x}}}),_a=new $({props:{title:"metadata_update",local:"huggingface_hub.metadata_update ][ huggingface_hub.metadata_update",headingTag:"h3"}}),ja=new w({props:{name:"huggingface_hub.metadata_update",anchor:"huggingface_hub.metadata_update",parameters:[{name:"repo_id",val:": str"},{name:"metadata",val:": Dict"},{name:"repo_type",val:": Optional = None"},{name:"overwrite",val:": bool = False"},{name:"token",val:": Optional = None"},{name:"commit_message",val:": Optional = None"},{name:"commit_description",val:": Optional = None"},{name:"revision",val:": Optional = None"},{name:"create_pr",val:": bool = False"},{name:"parent_commit",val:": Optional = None"}],parametersDescription:[{anchor:"huggingface_hub.metadata_update.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) &#x2014;
The name of the repository.`,name:"repo_id"},{anchor:"huggingface_hub.metadata_update.metadata",description:`<strong>metadata</strong> (<code>dict</code>) &#x2014;
A dictionary containing the metadata to be updated.`,name:"metadata"},{anchor:"huggingface_hub.metadata_update.repo_type",description:`<strong>repo_type</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Set to <code>&quot;dataset&quot;</code> or <code>&quot;space&quot;</code> if updating to a dataset or space,
<code>None</code> or <code>&quot;model&quot;</code> if updating to a model. Default is <code>None</code>.`,name:"repo_type"},{anchor:"huggingface_hub.metadata_update.overwrite",description:`<strong>overwrite</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) &#x2014;
If set to <code>True</code> an existing field can be overwritten, otherwise
attempting to overwrite an existing field will cause an error.`,name:"overwrite"},{anchor:"huggingface_hub.metadata_update.token",description:`<strong>token</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The Hugging Face authentication token.`,name:"token"},{anchor:"huggingface_hub.metadata_update.commit_message",description:`<strong>commit_message</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The summary / title / first line of the generated commit. Defaults to
<code>f&quot;Update metadata with huggingface_hub&quot;</code>`,name:"commit_message"},{anchor:"huggingface_hub.metadata_update.commit_description",description:`<strong>commit_description</strong> (<code>str</code> <em>optional</em>) &#x2014;
The description of the generated commit`,name:"commit_description"},{anchor:"huggingface_hub.metadata_update.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The git revision to commit from. Defaults to the head of the
<code>&quot;main&quot;</code> branch.`,name:"revision"},{anchor:"huggingface_hub.metadata_update.create_pr",description:`<strong>create_pr</strong> (<code>boolean</code>, <em>optional</em>) &#x2014;
Whether or not to create a Pull Request from <code>revision</code> with that commit.
Defaults to <code>False</code>.`,name:"create_pr"},{anchor:"huggingface_hub.metadata_update.parent_commit",description:`<strong>parent_commit</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
If specified and <code>create_pr</code> is <code>False</code>, the commit will fail if <code>revision</code> does not point to <code>parent_commit</code>.
If specified and <code>create_pr</code> is <code>True</code>, the pull request will be created from <code>parent_commit</code>.
Specifying <code>parent_commit</code> ensures the repo has not changed before committing the changes, and can be
especially useful if the repo is updated / committed to concurrently.`,name:"parent_commit"}],source:"https://github.com/huggingface/huggingface_hub/blob/vr_2402/src/huggingface_hub/repocard.py#L682",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>URL of the commit which updated the card metadata.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>str</code></p>
`}}),be=new F({props:{anchor:"huggingface_hub.metadata_update.example",$$slots:{default:[Pn]},$$scope:{ctx:x}}}),ya=new 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