import{S as ms,i as ps,s as ds,e as l,k as m,w as O,t as s,M as fs,c as o,d as t,m as p,a as i,x as V,h as r,b as u,N as xt,G as a,g as c,y as W,L as hs,q as X,o as U,B as K,v as gs}from"../../chunks/vendor-hf-doc-builder.js";import{I as qt}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{C as yt}from"../../chunks/CodeBlock-hf-doc-builder.js";import{C as vs}from"../../chunks/CourseFloatingBanner-hf-doc-builder.js";function bs($t){let P,Ae,k,j,re,S,sa,Q,ra,le,la,Be,C,Ge,d,oa,oe,ia,na,ie,ua,ca,ne,ma,pa,ue,da,fa,ce,ha,ga,me,va,ba,Se,T,M,pe,J,Ea,Y,wa,de,_a,Ce,w,xa,fe,qa,ya,he,$a,Pa,Z,ka,Ta,Je,h,Ha,ge,ja,Ma,ve,Ia,Aa,be,Ba,Ga,F,Sa,Ca,Fe,z,ze,ee,Ja,Le,v,Pt,Ne,q,Fa,L,za,La,Ee,Na,Ra,Re,H,I,we,N,Da,ae,Oa,_e,Va,De,f,Wa,xe,Xa,Ua,qe,Ka,Qa,ye,Ya,Za,$e,et,at,Pe,tt,st,Oe,A,rt,ke,lt,ot,Ve,R,We,b,kt,Xe,y,it,Te,nt,ut,He,ct,mt,Ue,D,Ke,E,Tt,Qe,_,pt,je,dt,ft,Me,ht,gt,Ie,vt,bt,Ye;return S=new qt({}),C=new vs({props:{chapter:9,classNames:"absolute z-10 right-0 top-0",notebooks:[{label:"English",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/en/chapter9/section5.ipynb"},{label:"Fran\xE7ais",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/fr/chapter9/section5.ipynb"},{label:"English",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/master/course/en/chapter9/section5.ipynb"},{label:"Fran\xE7ais",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/master/course/fr/chapter9/section5.ipynb"}]}}),J=new qt({}),z=new yt({props:{code:`import gradio as gr

title = "GPT-J-6B"
description = "Gradio Demo for GPT-J 6B, a transformer model trained using Ben Wang's Mesh Transformer JAX. 'GPT-J' refers to the class of model, while '6B' represents the number of trainable parameters. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
# D\xE9mo Gradio pour GPT-J 6B, un mod\xE8le de transformer entra\xEEn\xE9 avec le Mesh Transformer JAX de Ben Wang. GPT-J fait r\xE9f\xE9rence \xE0 la classe du mod\xE8le, tandis que '6B' repr\xE9sente le nombre de param\xE8tres entra\xEEnables. Pour l'utiliser, il suffit d'ajouter votre texte, ou de cliquer sur l'un des exemples pour le charger. Pour en savoir plus, consultez les liens ci-dessous.
article = "<p style='text-align: center'><a href='https://github.com/kingoflolz/mesh-transformer-jax' target='_blank'>GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model</a></p>"
# GPT-J-6B : Un mod\xE8le linguistique autor\xE9gressif \xE0 6 milliards de param\xE8tres
examples = [
    ["The tower is 324 metres (1,063 ft) tall,"],
    # La tour mesure 324 m\xE8tres (1 063 pieds) de haut,
    ["The Moon's orbit around Earth has"],
    # L'orbite de la Lune autour de la Terre a
    ["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
    # Le bassin de Borealis dans l'h\xE9misph\xE8re nord couvre 40 %.
]
gr.Interface.load(
    "huggingface/EleutherAI/gpt-j-6B",
    inputs=gr.Textbox(lines=5, label="Input Text"),
    title=title,
    description=description,
    article=article,
    examples=examples,
    enable_queue=True,
).launch()`,highlighted:`<span class="hljs-keyword">import</span> gradio <span class="hljs-keyword">as</span> gr

title = <span class="hljs-string">&quot;GPT-J-6B&quot;</span>
description = <span class="hljs-string">&quot;Gradio Demo for GPT-J 6B, a transformer model trained using Ben Wang&#x27;s Mesh Transformer JAX. &#x27;GPT-J&#x27; refers to the class of model, while &#x27;6B&#x27; represents the number of trainable parameters. To use it, simply add your text, or click one of the examples to load them. Read more at the links below.&quot;</span>
<span class="hljs-comment"># D\xE9mo Gradio pour GPT-J 6B, un mod\xE8le de transformer entra\xEEn\xE9 avec le Mesh Transformer JAX de Ben Wang. GPT-J fait r\xE9f\xE9rence \xE0 la classe du mod\xE8le, tandis que &#x27;6B&#x27; repr\xE9sente le nombre de param\xE8tres entra\xEEnables. Pour l&#x27;utiliser, il suffit d&#x27;ajouter votre texte, ou de cliquer sur l&#x27;un des exemples pour le charger. Pour en savoir plus, consultez les liens ci-dessous.</span>
article = <span class="hljs-string">&quot;&lt;p style=&#x27;text-align: center&#x27;&gt;&lt;a href=&#x27;https://github.com/kingoflolz/mesh-transformer-jax&#x27; target=&#x27;_blank&#x27;&gt;GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model&lt;/a&gt;&lt;/p&gt;&quot;</span>
<span class="hljs-comment"># GPT-J-6B : Un mod\xE8le linguistique autor\xE9gressif \xE0 6 milliards de param\xE8tres</span>
examples = [
    [<span class="hljs-string">&quot;The tower is 324 metres (1,063 ft) tall,&quot;</span>],
    <span class="hljs-comment"># La tour mesure 324 m\xE8tres (1 063 pieds) de haut,</span>
    [<span class="hljs-string">&quot;The Moon&#x27;s orbit around Earth has&quot;</span>],
    <span class="hljs-comment"># L&#x27;orbite de la Lune autour de la Terre a</span>
    [<span class="hljs-string">&quot;The smooth Borealis basin in the Northern Hemisphere covers 40%&quot;</span>],
    <span class="hljs-comment"># Le bassin de Borealis dans l&#x27;h\xE9misph\xE8re nord couvre 40 %.</span>
]
gr.Interface.load(
    <span class="hljs-string">&quot;huggingface/EleutherAI/gpt-j-6B&quot;</span>,
    inputs=gr.Textbox(lines=<span class="hljs-number">5</span>, label=<span class="hljs-string">&quot;Input Text&quot;</span>),
    title=title,
    description=description,
    article=article,
    examples=examples,
    enable_queue=<span class="hljs-literal">True</span>,
).launch()`}}),N=new qt({}),R=new yt({props:{code:'gr.Interface.load("spaces/abidlabs/remove-bg").launch()',highlighted:'gr.Interface.load(<span class="hljs-string">&quot;spaces/abidlabs/remove-bg&quot;</span>).launch()'}}),D=new yt({props:{code:`gr.Interface.load(
    "spaces/abidlabs/remove-bg", inputs="webcam", title="Remove your webcam background!"
).launch()`,highlighted:`gr.Interface.load(
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