import{s as Dn,o as Rn,n as E}from"../chunks/scheduler.6062bdaf.js";import{S as kn,i as En,g as p,s as o,r as m,A as Nn,h as d,f as a,c as r,j as J,u as h,x as C,k as x,y as i,a as c,v as u,d as M,t as f,w as y,m as $n,n as In}from"../chunks/index.4bca734e.js";import{T as An}from"../chunks/Tip.b9ac1f03.js";import{D as w}from"../chunks/Docstring.ed07512f.js";import{C as X}from"../chunks/CodeBlock.fa01571c.js";import{E as B}from"../chunks/ExampleCodeBlock.823fb173.js";import{H as $}from"../chunks/Heading.723dceba.js";function Zn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Wn(U){let n,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=$n(`Raises the following error:
`),j=p("ul"),j.innerHTML=_},l(s){n=In(s,`Raises the following error:
`),j=d(s,"UL",{"data-svelte-h":!0}),C(j)!=="svelte-1ewksj3"&&(j.innerHTML=_)},m(s,g){c(s,n,g),c(s,j,g)},p:E,d(s){s&&(a(n),a(j))}}}function Gn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Yn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Qn(U){let n,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=$n(`Raises the following errors:
`),j=p("ul"),j.innerHTML=_},l(s){n=In(s,`Raises the following errors:
`),j=d(s,"UL",{"data-svelte-h":!0}),C(j)!=="svelte-brxevo"&&(j.innerHTML=_)},m(s,g){c(s,n,g),c(s,j,g)},p:E,d(s){s&&(a(n),a(j))}}}function Fn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Sn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Bn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Xn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Vn(U){let n,j="Example:",_,s,g;return s=new X({props:{code:"ZnJvbSUyMGh1Z2dpbmdmYWNlX2h1Yi5yZXBvY2FyZF9kYXRhJTIwaW1wb3J0JTIwbW9kZWxfaW5kZXhfdG9fZXZhbF9yZXN1bHRzJTBBJTIzJTIwRGVmaW5lJTIwYSUyMG1pbmltYWwlMjBtb2RlbCUyMGluZGV4JTBBbW9kZWxfaW5kZXglMjAlM0QlMjAlNUIlMEElMjAlMjAlMjAlMjAlN0IlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjJuYW1lJTIyJTNBJTIwJTIybXktY29vbC1tb2RlbCUyMiUyQyUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMnJlc3VsdHMlMjIlM0ElMjAlNUIlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlN0IlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjJ0YXNrJTIyJTNBJTIwJTdCJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIydHlwZSUyMiUzQSUyMCUyMmltYWdlLWNsYXNzaWZpY2F0aW9uJTIyJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTdEJTJDJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIyZGF0YXNldCUyMiUzQSUyMCU3QiUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMnR5cGUlMjIlM0ElMjAlMjJiZWFucyUyMiUyQyUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMm5hbWUlMjIlM0ElMjAlMjJCZWFucyUyMiUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCU3RCUyQyUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMm1ldHJpY3MlMjIlM0ElMjAlNUIlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlN0IlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjJ0eXBlJTIyJTNBJTIwJTIyYWNjdXJhY3klMjIlMkMlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjJ2YWx1ZSUyMiUzQSUyMDAuOSUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCU3RCUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCU1RCUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCU3RCUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMCU1RCUwQSUyMCUyMCUyMCUyMCU3RCUwQSU1RCUwQW1vZGVsX25hbWUlMkMlMjBldmFsX3Jlc3VsdHMlMjAlM0QlMjBtb2RlbF9pbmRleF90b19ldmFsX3Jlc3VsdHMobW9kZWxfaW5kZXgpJTBBbW9kZWxfbmFtZSUwQWV2YWxfcmVzdWx0cyU1QjAlNUQudGFza190eXBlJTBBZXZhbF9yZXN1bHRzJTVCMCU1RC5tZXRyaWNfdHlwZSUwQQ==",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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Ln(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function Hn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function qn(U){let n,j="Example:",_,s,g;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=p("p"),n.textContent=j,_=o(),m(s.$$.fragment)},l(t){n=d(t,"P",{"data-svelte-h":!0}),C(n)!=="svelte-11lpom8"&&(n.textContent=j),_=r(t),h(s.$$.fragment,t)},m(t,b){c(t,n,b),c(t,_,b),u(s,t,b),g=!0},p:E,i(t){g||(M(s.$$.fragment,t),g=!0)},o(t){f(s.$$.fragment,t),g=!1},d(t){t&&(a(n),a(_)),y(s,t)}}}function zn(U){let n,j,_,s,g,t,b,Ls=`The huggingface_hub library provides a Python interface to create, share, and update Model/Dataset Cards.
Visit the <a href="https://huggingface.co/docs/hub/models-cards" rel="nofollow">dedicated documentation page</a> for a deeper view of what
Model Cards on the Hub are, and how they work under the hood. You can also check out our <a href="../how-to-model-cards">Model Cards guide</a> to
get a feel for how you would use these utilities in your own projects.`,ra,Te,ia,ve,Hs='The <code>RepoCard</code> object is the parent class of <a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.ModelCard">ModelCard</a>, <a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.DatasetCard">DatasetCard</a> and <code>SpaceCard</code>.',ca,v,Ae,Xa,N,$e,Va,wt,qs=`Initialize a RepoCard from string content. The content should be a
Markdown file with a YAML block at the beginning and a Markdown body.`,La,se,Ha,ne,qa,V,Ie,za,Tt,zs="Initialize a RepoCard from a template. By default, it uses the default template.",Pa,vt,Ps="Templates are Jinja2 templates that can be customized by passing keyword arguments.",Oa,L,De,Ka,At,Os="Initialize a RepoCard from a Hugging Face Hub repo’s README.md or a local filepath.",es,le,ts,oe,Re,as,$t,Ks="Push a RepoCard to a Hugging Face Hub repo.",ss,H,ke,ns,It,en="Save a RepoCard to a file.",ls,re,os,q,Ee,rs,Dt,tn=`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/v0.19.0/en/package_reference/cards#huggingface_hub.RepoCard.push_to_hub">huggingface_hub.repocard.RepoCard.push_to_hub()</a>.`,is,ie,pa,Ne,da,Ze,an='The <a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.CardData">CardData</a> object is the parent class of <a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.ModelCardData">ModelCardData</a> and <a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.DatasetCardData">DatasetCardData</a>.',ga,T,We,cs,Rt,sn="Structure containing metadata from a RepoCard.",ps,kt,nn='<a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.CardData">CardData</a> is the parent class of <a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.ModelCardData">ModelCardData</a> and <a href="/docs/huggingface_hub/v0.19.0/en/package_reference/cards#huggingface_hub.DatasetCardData">DatasetCardData</a>.',ds,Et,ln=`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.`,gs,ce,Ge,ms,Nt,on="Get value for a given metadata key.",hs,pe,Ye,us,Zt,rn="Pop value for a given metadata key.",Ms,de,Qe,fs,Wt,cn="Converts CardData to a dict.",ys,ge,Fe,_s,Gt,pn="Dumps CardData to a YAML block for inclusion in a README.md file.",ma,Se,ha,Be,ua,z,Xe,js,Z,Ve,bs,Yt,dn=`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>`,Cs,Qt,gn="Templates are Jinja2 templates that can be customized by passing keyword arguments.",Us,me,Ma,Le,fa,G,He,Js,Ft,mn="Model Card Metadata that is used by Hugging Face Hub when included at the top of your README.md",xs,he,ya,qe,_a,ze,hn="Dataset cards are also known as Data Cards in the ML Community.",ja,Pe,ba,P,Oe,ws,W,Ke,Ts,St,un=`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>`,vs,Bt,Mn="Templates are Jinja2 templates that can be customized by passing keyword arguments.",As,ue,Ca,et,Ua,O,tt,$s,Xt,fn="Dataset Card Metadata that is used by Hugging Face Hub when included at the top of your README.md",Ja,at,xa,st,wa,nt,lt,Ta,ot,va,D,rt,Is,Vt,yn="Space Card Metadata that is used by Hugging Face Hub when included at the top of your README.md",Ds,Lt,_n='To get an exhaustive reference of Spaces configuration, please visit <a href="https://huggingface.co/docs/hub/spaces-config-reference#spaces-configuration-reference" rel="nofollow">https://huggingface.co/docs/hub/spaces-config-reference#spaces-configuration-reference</a>.',Rs,Me,Aa,it,$a,ct,Ia,R,pt,ks,Ht,jn="Flattened representation of individual evaluation results found in model-index of Model Cards.",Es,qt,bn='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>.',Ns,fe,dt,Zs,zt,Cn=`Return True if <code>self</code> and <code>other</code> describe exactly the same metric but with a
different value.`,Da,gt,Ra,k,mt,Ws,Pt,Un="Takes in a model index and returns the model name and a list of <code>huggingface_hub.EvalResult</code> objects.",Gs,Ot,Jn=`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>`,Ys,ye,ka,ht,Ea,Y,ut,Qs,Kt,xn=`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,_e,Na,Mt,Za,Q,ft,Ss,ea,wn="Creates a metadata dict with the result from a model evaluated on a dataset.",Bs,je,Wa,yt,Ga,F,_t,Xs,ta,Tn=`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.`,Vs,be,Ya,oa,Qa;return g=new $({props:{title:"Repository Cards",local:"repository-cards",headingTag:"h1"}}),Te=new $({props:{title:"Repo Card",local:"huggingface_hub.RepoCard",headingTag:"h2"}}),Ae=new w({props:{name:"class huggingface_hub.RepoCard",anchor:"huggingface_hub.RepoCard",parameters:[{name:"content",val:": str"},{name:"ignore_metadata_errors",val:": bool = False"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.0/src/huggingface_hub/repocard.py#L37"}}),$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/v0.19.0/src/huggingface_hub/repocard.py#L42"}}),se=new B({props:{anchor:"huggingface_hub.RepoCard.__init__.example",$$slots:{default:[Zn]},$$scope:{ctx:U}}}),ne=new An({props:{$$slots:{default:[Wn]},$$scope:{ctx:U}}}),Ie=new w({props:{name:"from_template",anchor:"huggingface_hub.RepoCard.from_template",parameters:[{name:"card_data",val:": CardData"},{name:"template_path",val:": typing.Optional[str] = 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/v0.19.0/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/v0.19.0/en/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:": typing.Union[str, pathlib.Path]"},{name:"repo_type",val:": typing.Optional[str] = None"},{name:"token",val:": typing.Optional[str] = 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/v0.19.0/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/v0.19.0/en/package_reference/cards#huggingface_hub.RepoCard"
>huggingface_hub.repocard.RepoCard</a></p>
`}}),le=new B({props:{anchor:"huggingface_hub.RepoCard.load.example",$$slots:{default:[Gn]},$$scope:{ctx:U}}}),Re=new w({props:{name:"push_to_hub",anchor:"huggingface_hub.RepoCard.push_to_hub",parameters:[{name:"repo_id",val:": str"},{name:"token",val:": typing.Optional[str] = None"},{name:"repo_type",val:": typing.Optional[str] = None"},{name:"commit_message",val:": typing.Optional[str] = None"},{name:"commit_description",val:": typing.Optional[str] = None"},{name:"revision",val:": typing.Optional[str] = None"},{name:"create_pr",val:": typing.Optional[bool] = None"},{name:"parent_commit",val:": typing.Optional[str] = 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/v0.19.0/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>
`}}),ke=new w({props:{name:"save",anchor:"huggingface_hub.RepoCard.save",parameters:[{name:"filepath",val:": typing.Union[pathlib.Path, str]"}],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/v0.19.0/src/huggingface_hub/repocard.py#L116"}}),re=new B({props:{anchor:"huggingface_hub.RepoCard.save.example",$$slots:{default:[Yn]},$$scope:{ctx:U}}}),Ee=new w({props:{name:"validate",anchor:"huggingface_hub.RepoCard.validate",parameters:[{name:"repo_type",val:": typing.Optional[str] = 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/v0.19.0/src/huggingface_hub/repocard.py#L190"}}),ie=new An({props:{$$slots:{default:[Qn]},$$scope:{ctx:U}}}),Ne=new $({props:{title:"Card Data",local:"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/v0.19.0/src/huggingface_hub/repocard_data.py#L151"}}),Ge=new w({props:{name:"get",anchor:"huggingface_hub.CardData.get",parameters:[{name:"key",val:": str"},{name:"default",val:": typing.Any = None"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.0/src/huggingface_hub/repocard_data.py#L202"}}),Ye=new w({props:{name:"pop",anchor:"huggingface_hub.CardData.pop",parameters:[{name:"key",val:": str"},{name:"default",val:": typing.Any = None"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.0/src/huggingface_hub/repocard_data.py#L206"}}),Qe=new w({props:{name:"to_dict",anchor:"huggingface_hub.CardData.to_dict",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.0/src/huggingface_hub/repocard_data.py#L164",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>
`}}),Fe=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/v0.19.0/src/huggingface_hub/repocard_data.py#L184",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>
`}}),Se=new $({props:{title:"Model Cards",local:"model-cards",headingTag:"h2"}}),Be=new $({props:{title:"ModelCard",local:"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/v0.19.0/src/huggingface_hub/repocard.py#L330"}}),Ve=new w({props:{name:"from_template",anchor:"huggingface_hub.ModelCard.from_template",parameters:[{name:"card_data",val:": ModelCardData"},{name:"template_path",val:": typing.Optional[str] = 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/v0.19.0/src/huggingface_hub/repocard.py#L335",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/v0.19.0/en/package_reference/cards#huggingface_hub.ModelCard"
>huggingface_hub.ModelCard</a></p>
`}}),me=new B({props:{anchor:"huggingface_hub.ModelCard.from_template.example",$$slots:{default:[Fn]},$$scope:{ctx:U}}}),Le=new $({props:{title:"ModelCardData",local:"huggingface_hub.ModelCardData",headingTag:"h3"}}),He=new w({props:{name:"class huggingface_hub.ModelCardData",anchor:"huggingface_hub.ModelCardData",parameters:[{name:"language",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"license",val:": typing.Optional[str] = None"},{name:"library_name",val:": typing.Optional[str] = None"},{name:"tags",val:": typing.Optional[typing.List[str]] = None"},{name:"datasets",val:": typing.Optional[typing.List[str]] = None"},{name:"metrics",val:": typing.Optional[typing.List[str]] = None"},{name:"eval_results",val:": typing.Optional[typing.List[huggingface_hub.repocard_data.EvalResult]] = None"},{name:"model_name",val:": typing.Optional[str] = None"},{name:"ignore_metadata_errors",val:": bool = False"},{name:"**kwargs",val:""}],parametersDescription:[{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.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.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/hub-docs/blob/main/js/src/lib/interfaces/Libraries.ts" rel="nofollow">https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Libraries.ts</a>.
Defaults to None.`,name:"library_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.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.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.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.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.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/v0.19.0/src/huggingface_hub/repocard_data.py#L227"}}),he=new B({props:{anchor:"huggingface_hub.ModelCardData.example",$$slots:{default:[Sn]},$$scope:{ctx:U}}}),qe=new $({props:{title:"Dataset Cards",local:"dataset-cards",headingTag:"h2"}}),Pe=new $({props:{title:"DatasetCard",local:"huggingface_hub.DatasetCard",headingTag:"h3"}}),Oe=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/v0.19.0/src/huggingface_hub/repocard.py#L410"}}),Ke=new w({props:{name:"from_template",anchor:"huggingface_hub.DatasetCard.from_template",parameters:[{name:"card_data",val:": DatasetCardData"},{name:"template_path",val:": typing.Optional[str] = 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
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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/v0.19.0/src/huggingface_hub/repocard.py#L415",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/v0.19.0/en/package_reference/cards#huggingface_hub.DatasetCard"
>huggingface_hub.DatasetCard</a></p>
`}}),ue=new B({props:{anchor:"huggingface_hub.DatasetCard.from_template.example",$$slots:{default:[Bn]},$$scope:{ctx:U}}}),et=new $({props:{title:"DatasetCardData",local:"huggingface_hub.DatasetCardData",headingTag:"h3"}}),tt=new w({props:{name:"class huggingface_hub.DatasetCardData",anchor:"huggingface_hub.DatasetCardData",parameters:[{name:"language",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"license",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"annotations_creators",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"language_creators",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"multilinguality",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"size_categories",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"source_datasets",val:": typing.Optional[typing.List[str]] = None"},{name:"task_categories",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"task_ids",val:": typing.Union[typing.List[str], str, NoneType] = None"},{name:"paperswithcode_id",val:": typing.Optional[str] = None"},{name:"pretty_name",val:": typing.Optional[str] = None"},{name:"train_eval_index",val:": typing.Optional[typing.Dict] = None"},{name:"config_names",val:": typing.Union[typing.List[str], str, NoneType] = 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;
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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.
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A list of the available dataset configs for the dataset.`,name:"config_names"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.0/src/huggingface_hub/repocard_data.py#L333"}}),at=new $({props:{title:"Space Cards",local:"space-cards",headingTag:"h2"}}),st=new $({props:{title:"SpaceCard",local:"huggingface_hub.SpaceCard",headingTag:"h3"}}),lt=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/v0.19.0/src/huggingface_hub/repocard.py#L474"}}),ot=new $({props:{title:"SpaceCardData",local:"huggingface_hub.SpaceCardData",headingTag:"h3"}}),rt=new w({props:{name:"class huggingface_hub.SpaceCardData",anchor:"huggingface_hub.SpaceCardData",parameters:[{name:"title",val:": typing.Optional[str] = None"},{name:"sdk",val:": typing.Optional[str] = None"},{name:"sdk_version",val:": typing.Optional[str] = None"},{name:"python_version",val:": typing.Optional[str] = None"},{name:"app_file",val:": typing.Optional[str] = None"},{name:"app_port",val:": typing.Optional[int] = None"},{name:"license",val:": typing.Optional[str] = None"},{name:"duplicated_from",val:": typing.Optional[str] = None"},{name:"models",val:": typing.Optional[typing.List[str]] = None"},{name:"datasets",val:": typing.Optional[typing.List[str]] = None"},{name:"tags",val:": typing.Optional[typing.List[str]] = 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/v0.19.0/src/huggingface_hub/repocard_data.py#L413"}}),Me=new B({props:{anchor:"huggingface_hub.SpaceCardData.example",$$slots:{default:[Xn]},$$scope:{ctx:U}}}),it=new $({props:{title:"Utilities",local:"utilities",headingTag:"h2"}}),ct=new $({props:{title:"EvalResult",local:"huggingface_hub.EvalResult",headingTag:"h3"}}),pt=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:": typing.Any"},{name:"task_name",val:": typing.Optional[str] = None"},{name:"dataset_config",val:": typing.Optional[str] = None"},{name:"dataset_split",val:": typing.Optional[str] = None"},{name:"dataset_revision",val:": typing.Optional[str] = None"},{name:"dataset_args",val:": typing.Union[typing.Dict[str, typing.Any], NoneType] = None"},{name:"metric_name",val:": typing.Optional[str] = None"},{name:"metric_config",val:": typing.Optional[str] = None"},{name:"metric_args",val:": typing.Union[typing.Dict[str, typing.Any], NoneType] = None"},{name:"verified",val:": typing.Optional[bool] = None"},{name:"verify_token",val:": typing.Optional[str] = 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"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.0/src/huggingface_hub/repocard_data.py#L15"}}),dt=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/v0.19.0/src/huggingface_hub/repocard_data.py#L135"}}),gt=new $({props:{title:"model_index_to_eval_results",local:"huggingface_hub.repocard_data.model_index_to_eval_results",headingTag:"h3"}}),mt=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:": typing.List[typing.Dict[str, typing.Any]]"}],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/v0.19.0/src/huggingface_hub/repocard_data.py#L494",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>
`}}),ye=new B({props:{anchor:"huggingface_hub.repocard_data.model_index_to_eval_results.example",$$slots:{default:[Vn]},$$scope:{ctx:U}}}),ht=new $({props:{title:"eval_results_to_model_index",local:"huggingface_hub.repocard_data.eval_results_to_model_index",headingTag:"h3"}}),ut=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:": typing.List[huggingface_hub.repocard_data.EvalResult]"}],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
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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/v0.19.0/src/huggingface_hub/repocard_data.py#L606",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>
`}}),_e=new B({props:{anchor:"huggingface_hub.repocard_data.eval_results_to_model_index.example",$$slots:{default:[Ln]},$$scope:{ctx:U}}}),Mt=new $({props:{title:"metadata_eval_result",local:"huggingface_hub.metadata_eval_result",headingTag:"h3"}}),ft=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:": typing.Any"},{name:"dataset_pretty_name",val:": str"},{name:"dataset_id",val:": str"},{name:"metrics_config",val:": typing.Optional[str] = None"},{name:"metrics_verified",val:": bool = False"},{name:"dataset_config",val:": typing.Optional[str] = None"},{name:"dataset_split",val:": typing.Optional[str] = None"},{name:"dataset_revision",val:": typing.Optional[str] = None"},{name:"metrics_verification_token",val:": typing.Optional[str] = None"}],parametersDescription:[{anchor:"huggingface_hub.metadata_eval_result.model_pretty_name",description:`<strong>model_pretty_name</strong> (<code>str</code>) &#x2014;
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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/v0.19.0/src/huggingface_hub/repocard.py#L546",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>
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Whether or not to create a Pull Request from <code>revision</code> with that commit.
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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/v0.19.0/src/huggingface_hub/repocard.py#L674",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>
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