import{s as Tt,o as Ct,n as wt}from"../chunks/scheduler.6062bdaf.js";import{S as kt,i as Ht,g as i,s as t,r as l,A as Lt,h as o,f as r,c as a,j as E,u as h,x as p,k as I,y as n,a as s,v as u,d as m,t as _,w as b}from"../chunks/index.4bca734e.js";import{H as Oe,g as Mt}from"../chunks/Heading.8904b53b.js";import{T as Pt}from"../chunks/Tip.b9ac1f03.js";import{D as x}from"../chunks/Docstring.5a52fa73.js";import{C as At}from"../chunks/CodeBlock.fa01571c.js";import{E as jt}from"../chunks/ExampleCodeBlock.5dee3e03.js";function qt(_e){let d,M='Check out the <a href="../guides/inference_endpoints">related guide</a> to learn how to use <code>huggingface_hub</code> to manage your Inference Endpoints programmatically.';return{c(){d=i("p"),d.innerHTML=M},l($){d=o($,"P",{"data-svelte-h":!0}),p(d)!=="svelte-tmb85g"&&(d.innerHTML=M)},m($,y){s($,d,y)},p:wt,d($){$&&r(d)}}}function zt(_e){let d,M="Example:",$,y,w;return y=new At({props:{code:"ZnJvbSUyMGh1Z2dpbmdmYWNlX2h1YiUyMGltcG9ydCUyMGdldF9pbmZlcmVuY2VfZW5kcG9pbnQlMEFlbmRwb2ludCUyMCUzRCUyMGdldF9pbmZlcmVuY2VfZW5kcG9pbnQoJTIybXktdGV4dC10by1pbWFnZSUyMiklMEFlbmRwb2ludCUwQSUwQWVuZHBvaW50LnN0YXR1cyUwQWVuZHBvaW50LnVybCUwQSUwQWVuZHBvaW50LmNsaWVudC50ZXh0X3RvX2ltYWdlKC4uLiklMEElMEFlbmRwb2ludC5wYXVzZSgpJTBBJTBBZW5kcG9pbnQucmVzdW1lKCklMEFlbmRwb2ludC53YWl0KCklMEFlbmRwb2ludC5jbGllbnQudGV4dF90b19pbWFnZSguLi4p",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> get_inference_endpoint
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint = get_inference_endpoint(<span class="hljs-string">&quot;my-text-to-image&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint
InferenceEndpoint(name=<span class="hljs-string">&#x27;my-text-to-image&#x27;</span>, ...)

<span class="hljs-comment"># Get status</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint.status
<span class="hljs-string">&#x27;running&#x27;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint.url
<span class="hljs-string">&#x27;https://my-text-to-image.region.vendor.endpoints.huggingface.cloud&#x27;</span>

<span class="hljs-comment"># Run inference</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint.client.text_to_image(...)

<span class="hljs-comment"># Pause endpoint to save $$$</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint.pause()

<span class="hljs-comment"># ...</span>
<span class="hljs-comment"># Resume and wait for deployment</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint.resume()
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint.wait()
<span class="hljs-meta">&gt;&gt;&gt; </span>endpoint.client.text_to_image(...)`,wrap:!1}}),{c(){d=i("p"),d.textContent=M,$=t(),l(y.$$.fragment)},l(v){d=o(v,"P",{"data-svelte-h":!0}),p(d)!=="svelte-11lpom8"&&(d.textContent=M),$=a(v),h(y.$$.fragment,v)},m(v,L){s(v,d,L),s(v,$,L),u(y,v,L),w=!0},p:wt,i(v){w||(m(y.$$.fragment,v),w=!0)},o(v){_(y.$$.fragment,v),w=!1},d(v){v&&(r(d),r($)),b(y,v)}}}function Dt(_e){let d,M,$,y,w,v,L,Yn='Inference Endpoints provides a secure production solution to easily deploy models on a dedicated and autoscaling infrastructure managed by Hugging Face. An Inference Endpoint is built from a model from the <a href="https://huggingface.co/models" rel="nofollow">Hub</a>. This page is a reference for <code>huggingface_hub</code>’s integration with Inference Endpoints. For more information about the Inference Endpoints product, check out its <a href="https://huggingface.co/docs/inference-endpoints/index" rel="nofollow">official documentation</a>.',Ge,D,Ze,Z,Xn='Inference Endpoints can be fully managed via API. The endpoints are documented with <a href="https://api.endpoints.huggingface.cloud/" rel="nofollow">Swagger</a>. The <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint">InferenceEndpoint</a> class is a simple wrapper built on top on this API.',Be,B,Qe,Q,Jn='A subset of the Inference Endpoint features are implemented in <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi">HfApi</a>:',Ye,Y,Kn='<li><a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.get_inference_endpoint">get_inference_endpoint()</a> and <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.list_inference_endpoints">list_inference_endpoints()</a> to get information about your Inference Endpoints</li> <li><a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.create_inference_endpoint">create_inference_endpoint()</a>, <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.update_inference_endpoint">update_inference_endpoint()</a> and <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.delete_inference_endpoint">delete_inference_endpoint()</a> to deploy and manage Inference Endpoints</li> <li><a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.pause_inference_endpoint">pause_inference_endpoint()</a> and <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.resume_inference_endpoint">resume_inference_endpoint()</a> to pause and resume an Inference Endpoint</li> <li><a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.scale_to_zero_inference_endpoint">scale_to_zero_inference_endpoint()</a> to manually scale an Endpoint to 0 replicas</li>',Xe,X,Je,J,et='The main dataclass is <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint">InferenceEndpoint</a>. It contains information about a deployed <code>InferenceEndpoint</code>, including its configuration and current state. Once deployed, you can run inference on the Endpoint using the  <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.client">InferenceEndpoint.client</a> and <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.async_client">InferenceEndpoint.async_client</a> properties that respectively return an <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_client#huggingface_hub.InferenceClient">InferenceClient</a> and an <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_client#huggingface_hub.AsyncInferenceClient">AsyncInferenceClient</a> object.',Ke,g,K,un,be,nt="Contains information about a deployed Inference Endpoint.",mn,V,_n,N,ee,bn,ve,tt="Initialize object from raw dictionary.",vn,S,ne,$n,$e,at="Returns a client to make predictions on this Inference Endpoint.",En,R,te,In,Ee,rt="Returns a client to make predictions on this Inference Endpoint.",yn,T,ae,xn,Ie,it="Delete the Inference Endpoint.",wn,ye,ot=`This operation is not reversible. If you don’t want to be charged for an Inference Endpoint, it is preferable
to pause it with <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.pause">InferenceEndpoint.pause()</a> or scale it to zero with <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.scale_to_zero">InferenceEndpoint.scale_to_zero()</a>.`,Tn,xe,ct='This is an alias for <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.delete_inference_endpoint">HfApi.delete_inference_endpoint()</a>.',Cn,U,re,kn,we,st="Fetch latest information about the Inference Endpoint.",Hn,C,ie,Ln,Te,gt="Pause the Inference Endpoint.",Mn,Ce,pt=`A paused Inference Endpoint will not be charged. It can be resumed at any time using <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.resume">InferenceEndpoint.resume()</a>.
This is different than scaling the Inference Endpoint to zero with <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.scale_to_zero">InferenceEndpoint.scale_to_zero()</a>, which
would be automatically restarted when a request is made to it.`,Pn,ke,ft=`This is an alias for <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.pause_inference_endpoint">HfApi.pause_inference_endpoint()</a>. The current object is mutated in place with the
latest data from the server.`,An,P,oe,jn,He,dt="Resume the Inference Endpoint.",qn,Le,lt=`This is an alias for <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.resume_inference_endpoint">HfApi.resume_inference_endpoint()</a>. The current object is mutated in place with the
latest data from the server.`,zn,k,ce,Dn,Me,ht="Scale Inference Endpoint to zero.",Vn,Pe,ut=`An Inference Endpoint scaled to zero will not be charged. It will be resume on the next request to it, with a
cold start delay. This is different than pausing the Inference Endpoint with <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.pause">InferenceEndpoint.pause()</a>, which
would require a manual resume with <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint.resume">InferenceEndpoint.resume()</a>.`,Nn,Ae,mt=`This is an alias for <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.scale_to_zero_inference_endpoint">HfApi.scale_to_zero_inference_endpoint()</a>. The current object is mutated in place with the
latest data from the server.`,Sn,H,se,Rn,je,_t="Update the Inference Endpoint.",Un,qe,bt=`This method allows the update of either the compute configuration, the deployed model, or both. All arguments are
optional but at least one must be provided.`,Wn,ze,vt=`This is an alias for <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.HfApi.update_inference_endpoint">HfApi.update_inference_endpoint()</a>. The current object is mutated in place with the
latest data from the server.`,On,A,ge,Fn,De,$t="Wait for the Inference Endpoint to be deployed.",Gn,Ve,Et=`Information from the server will be fetched every 1s. If the Inference Endpoint is not deployed after <code>timeout</code>
seconds, a <code>InferenceEndpointTimeoutError</code> will be raised. The <a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpoint">InferenceEndpoint</a> will be mutated in place with the latest
data.`,en,pe,nn,j,fe,Zn,Ne,It="An enumeration.",tn,de,an,q,le,Bn,Se,yt="An enumeration.",rn,he,on,z,ue,Qn,Re,xt="Generic exception when dealing with Inference Endpoints.",cn,Fe,sn;return w=new Oe({props:{title:"Inference Endpoints",local:"inference-endpoints",headingTag:"h1"}}),D=new Pt({props:{$$slots:{default:[qt]},$$scope:{ctx:_e}}}),B=new Oe({props:{title:"Methods",local:"methods",headingTag:"h2"}}),X=new Oe({props:{title:"InferenceEndpoint",local:"huggingface_hub.InferenceEndpoint",headingTag:"h2"}}),K=new x({props:{name:"class huggingface_hub.InferenceEndpoint",anchor:"huggingface_hub.InferenceEndpoint",parameters:[{name:"namespace",val:": str"},{name:"raw",val:": typing.Dict"},{name:"_token",val:": typing.Optional[str]"},{name:"_api",val:": HfApi"}],parametersDescription:[{anchor:"huggingface_hub.InferenceEndpoint.name",description:`<strong>name</strong> (<code>str</code>) &#x2014;
The unique name of the Inference Endpoint.`,name:"name"},{anchor:"huggingface_hub.InferenceEndpoint.namespace",description:`<strong>namespace</strong> (<code>str</code>) &#x2014;
The namespace where the Inference Endpoint is located.`,name:"namespace"},{anchor:"huggingface_hub.InferenceEndpoint.repository",description:`<strong>repository</strong> (<code>str</code>) &#x2014;
The name of the model repository deployed on this Inference Endpoint.`,name:"repository"},{anchor:"huggingface_hub.InferenceEndpoint.status",description:`<strong>status</strong> (<a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpointStatus">InferenceEndpointStatus</a>) &#x2014;
The current status of the Inference Endpoint.`,name:"status"},{anchor:"huggingface_hub.InferenceEndpoint.url",description:`<strong>url</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The URL of the Inference Endpoint, if available. Only a deployed Inference Endpoint will have a URL.`,name:"url"},{anchor:"huggingface_hub.InferenceEndpoint.framework",description:`<strong>framework</strong> (<code>str</code>) &#x2014;
The machine learning framework used for the model.`,name:"framework"},{anchor:"huggingface_hub.InferenceEndpoint.revision",description:`<strong>revision</strong> (<code>str</code>) &#x2014;
The specific model revision deployed on the Inference Endpoint.`,name:"revision"},{anchor:"huggingface_hub.InferenceEndpoint.task",description:`<strong>task</strong> (<code>str</code>) &#x2014;
The task associated with the deployed model.`,name:"task"},{anchor:"huggingface_hub.InferenceEndpoint.created_at",description:`<strong>created_at</strong> (<code>datetime.datetime</code>) &#x2014;
The timestamp when the Inference Endpoint was created.`,name:"created_at"},{anchor:"huggingface_hub.InferenceEndpoint.updated_at",description:`<strong>updated_at</strong> (<code>datetime.datetime</code>) &#x2014;
The timestamp of the last update of the Inference Endpoint.`,name:"updated_at"},{anchor:"huggingface_hub.InferenceEndpoint.type",description:`<strong>type</strong> (<a href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpointType">InferenceEndpointType</a>) &#x2014;
The type of the Inference Endpoint (public, protected, private).`,name:"type"},{anchor:"huggingface_hub.InferenceEndpoint.raw",description:`<strong>raw</strong> (<code>Dict</code>) &#x2014;
The raw dictionary data returned from the API.`,name:"raw"},{anchor:"huggingface_hub.InferenceEndpoint.token",description:`<strong>token</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Authentication token for the Inference Endpoint, if set when requesting the API.`,name:"token"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L45"}}),V=new jt({props:{anchor:"huggingface_hub.InferenceEndpoint.example",$$slots:{default:[zt]},$$scope:{ctx:_e}}}),ee=new x({props:{name:"from_raw",anchor:"huggingface_hub.InferenceEndpoint.from_raw",parameters:[{name:"raw",val:": typing.Dict"},{name:"namespace",val:": str"},{name:"token",val:": typing.Optional[str] = None"},{name:"api",val:": typing.Optional[ForwardRef('HfApi')] = None"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L126"}}),ne=new x({props:{name:"client",anchor:"huggingface_hub.InferenceEndpoint.client",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L145",raiseDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<ul>
<li><a
  href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpointError"
>InferenceEndpointError</a> — If the Inference Endpoint is not yet deployed.</li>
</ul>
`,raiseType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><a
  href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpointError"
>InferenceEndpointError</a></p>
`}}),te=new x({props:{name:"async_client",anchor:"huggingface_hub.InferenceEndpoint.async_client",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L159",raiseDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<ul>
<li><a
  href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpointError"
>InferenceEndpointError</a> — If the Inference Endpoint is not yet deployed.</li>
</ul>
`,raiseType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><a
  href="/docs/huggingface_hub/v0.19.3/en/package_reference/inference_endpoints#huggingface_hub.InferenceEndpointError"
>InferenceEndpointError</a></p>
`}}),ae=new x({props:{name:"delete",anchor:"huggingface_hub.InferenceEndpoint.delete",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L321"}}),re=new x({props:{name:"fetch",anchor:"huggingface_hub.InferenceEndpoint.fetch",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L208"}}),ie=new x({props:{name:"pause",anchor:"huggingface_hub.InferenceEndpoint.pause",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L280"}}),oe=new x({props:{name:"resume",anchor:"huggingface_hub.InferenceEndpoint.resume",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L295"}}),ce=new x({props:{name:"scale_to_zero",anchor:"huggingface_hub.InferenceEndpoint.scale_to_zero",parameters:[],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L306"}}),se=new x({props:{name:"update",anchor:"huggingface_hub.InferenceEndpoint.update",parameters:[{name:"accelerator",val:": typing.Optional[str] = None"},{name:"instance_size",val:": typing.Optional[str] = None"},{name:"instance_type",val:": typing.Optional[str] = None"},{name:"min_replica",val:": typing.Optional[int] = None"},{name:"max_replica",val:": typing.Optional[int] = None"},{name:"repository",val:": typing.Optional[str] = None"},{name:"framework",val:": typing.Optional[str] = None"},{name:"revision",val:": typing.Optional[str] = None"},{name:"task",val:": typing.Optional[str] = None"}],parametersDescription:[{anchor:"huggingface_hub.InferenceEndpoint.update.accelerator",description:`<strong>accelerator</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The hardware accelerator to be used for inference (e.g. <code>&quot;cpu&quot;</code>).`,name:"accelerator"},{anchor:"huggingface_hub.InferenceEndpoint.update.instance_size",description:`<strong>instance_size</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The size or type of the instance to be used for hosting the model (e.g. <code>&quot;large&quot;</code>).`,name:"instance_size"},{anchor:"huggingface_hub.InferenceEndpoint.update.instance_type",description:`<strong>instance_type</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The cloud instance type where the Inference Endpoint will be deployed (e.g. <code>&quot;c6i&quot;</code>).`,name:"instance_type"},{anchor:"huggingface_hub.InferenceEndpoint.update.min_replica",description:`<strong>min_replica</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The minimum number of replicas (instances) to keep running for the Inference Endpoint.`,name:"min_replica"},{anchor:"huggingface_hub.InferenceEndpoint.update.max_replica",description:`<strong>max_replica</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The maximum number of replicas (instances) to scale to for the Inference Endpoint.`,name:"max_replica"},{anchor:"huggingface_hub.InferenceEndpoint.update.repository",description:`<strong>repository</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The name of the model repository associated with the Inference Endpoint (e.g. <code>&quot;gpt2&quot;</code>).`,name:"repository"},{anchor:"huggingface_hub.InferenceEndpoint.update.framework",description:`<strong>framework</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The machine learning framework used for the model (e.g. <code>&quot;custom&quot;</code>).`,name:"framework"},{anchor:"huggingface_hub.InferenceEndpoint.update.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The specific model revision to deploy on the Inference Endpoint (e.g. <code>&quot;6c0e6080953db56375760c0471a8c5f2929baf11&quot;</code>).`,name:"revision"},{anchor:"huggingface_hub.InferenceEndpoint.update.task",description:`<strong>task</strong> (<code>str</code>, <em>optional</em>) &#x2014;
The task on which to deploy the model (e.g. <code>&quot;text-classification&quot;</code>).`,name:"task"}],source:"https://github.com/huggingface/huggingface_hub/blob/v0.19.3/src/huggingface_hub/_inference_endpoints.py#L215"}}),ge=new x({props:{name:"wait",anchor:"huggingface_hub.InferenceEndpoint.wait",parameters:[{name:"timeout",val:": typing.Optional[int] = None"},{name:"refresh_every",val:": int = 5"}],parametersDescription:[{anchor:"huggingface_hub.InferenceEndpoint.wait.timeout",description:`<strong>timeout</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The maximum time to wait for the Inference Endpoint to be deployed, in seconds. If <code>None</code>, will wait
indefinitely.`,name:"timeout"},{anchor:"huggingface_hub.InferenceEndpoint.wait.refresh_every",description:`<strong>refresh_every</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The time to wait between each fetch of the Inference Endpoint status, in seconds. 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