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yt({props:{$$slots:{default:[Kl]},$$scope:{ctx:i}}}),{c(){L(e.$$.fragment)},l(t){J(e.$$.fragment,t)},m(t,l){H(e,t,l),s=!0},p(t,l){const r={};l&2&&(r.$$scope={dirty:l,ctx:t}),e.$set(r)},i(t){s||(v(e.$$.fragment,t),s=!0)},o(t){b(e.$$.fragment,t),s=!1},d(t){I(e,t)}}}function Wl(i){let e,s="Você deve deixar a pasta <code>diffusers</code> se você quiser continuar usando a biblioteca.";return{c(){e=k("p"),e.innerHTML=s},l(t){e=T(t,"P",{"data-svelte-h":!0}),U(e)!=="svelte-1x7dske"&&(e.innerHTML=s)},m(t,l){c(t,e,l)},p:B,d(t){t&&n(e)}}}function Ql(i){let e,s,t,l,r,u,m,d="🤗 Diffusers é testado no Python 3.8+, PyTorch 1.7.0+, e Flax. Siga as instruções de instalação abaixo para a biblioteca de deep learning que você está utilizando:",E,M,C='<li><a href="https://pytorch.org/get-started/locally/" rel="nofollow">PyTorch</a> instruções de instalação</li> <li><a href="https://flax.readthedocs.io/en/latest/" rel="nofollow">Flax</a> instruções de instalação</li>',j,y,A,R,Y=`Recomenda-se instalar 🤗 Diffusers em um <a href="https://docs.python.org/3/library/venv.html" rel="nofollow">ambiente virtual</a>.
Se você não está familiarizado com ambiente virtuals, veja o <a href="https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/" rel="nofollow">guia</a>.
Um ambiente virtual deixa mais fácil gerenciar diferentes projetos e evitar problemas de compatibilidade entre dependências.`,z,P,q="Comece criando um ambiente virtual no diretório do projeto:",D,x,N,V,S="Ative o ambiente virtual:",W,Q,fe,X,_e="Recomenda-se a instalação do 🤗 Transformers porque 🤗 Diffusers depende de seus modelos:",ce,O,ae,F,ue,ee,we="Antes da instalação do 🤗 Diffusers a partir do código fonte, certifique-se de ter o PyTorch e o 🤗 Accelerate instalados.",pe,G,be="Para instalar o 🤗 Accelerate:",he,te,se,Z,We="então instale o 🤗 Diffusers do código fonte:",K,ne,Ce,oe,ie=`Esse comando instala a última versão em desenvolvimento <code>main</code> em vez da última versão estável <code>stable</code>.
A versão <code>main</code> é útil para se manter atualizado com os últimos desenvolvimentos.
Por exemplo, se um bug foi corrigido desde o último lançamento estável, mas um novo lançamento ainda não foi lançado.
No entanto, isso significa que a versão <code>main</code> pode não ser sempre estável.
Nós nos esforçamos para manter a versão <code>main</code> operacional, e a maioria dos problemas geralmente são resolvidos em algumas horas ou um dia.
Se você encontrar um problema, por favor abra uma <a href="https://github.com/huggingface/diffusers/issues/new/choose" rel="nofollow">Issue</a>, assim conseguimos arrumar o quanto antes!`,me,re,at,Te,It="Você precisará de uma instalação editável se você:",st,ze,Jt="<li>Usar a versão <code>main</code> do código fonte.</li> <li>Contribuir para o 🤗 Diffusers e precisa testar mudanças no código.</li>",nt,ye,jt="Clone o repositório e instale o 🤗 Diffusers com os seguintes comandos:",rt,Le,ot,Ee,it,He,Pt=`Esses comandos irá linkar a pasta que você clonou o repositório e os caminhos das suas bibliotecas Python.
Python então irá procurar dentro da pasta que você clonou além dos caminhos normais das bibliotecas.
Por exemplo, se o pacote python for tipicamente instalado no <code>~/anaconda3/envs/main/lib/python3.10/site-packages/</code>, o Python também irá procurar na pasta <code>~/diffusers/</code> que você clonou.`,ft,xe,ct,Ie,Nt="Agora você pode facilmente atualizar seu clone para a última versão do 🤗 Diffusers com o seguinte comando:",ut,Je,pt,je,St="Seu ambiente Python vai encontrar a versão <code>main</code> do 🤗 Diffusers na próxima execução.",ht,Pe,mt,Ne,Ut="Os pesos e os arquivos dos modelos são baixados do Hub para o cache que geralmente é o seu diretório home. Você pode mudar a localização do cache especificando as variáveis de ambiente <code>HF_HOME</code> ou <code>HUGGINFACE_HUB_CACHE</code> ou configurando o parâmetro <code>cache_dir</code> em métodos como <code>from_pretrained()</code>.",dt,Se,Zt="Aquivos em cache permitem que você rode 🤗 Diffusers offline. Para prevenir que o 🤗 Diffusers se conecte à internet, defina a variável de ambiente <code>HF_HUB_OFFLINE</code> para <code>True</code> e o 🤗 Diffusers irá apenas carregar arquivos previamente baixados em cache.",$t,Ue,gt,Ze,Rt='Para mais detalhes de como gerenciar e limpar o cache, olhe o guia de <a href="https://huggingface.co/docs/huggingface_hub/guides/manage-cache" rel="nofollow">caching</a>.',vt,Re,_t,Ve,Vt=`Nossa biblioteca coleta informações de telemetria durante as requisições <code>from_pretrained()</code>.
O dado coletado inclui a versão do 🤗 Diffusers e PyTorch/Flax, o modelo ou classe de pipeline requisitado,
e o caminho para um checkpoint pré-treinado se ele estiver hospedado no Hugging Face Hub.
Esse dado de uso nos ajuda a debugar problemas e priorizar novas funcionalidades.
Telemetria é enviada apenas quando é carregado modelos e pipelines do Hub,
e não é coletado se você estiver carregando arquivos locais.`,wt,Ae,At=`Nos entendemos que nem todo mundo quer compartilhar informações adicionais, e nós respeitamos sua privacidade.
Você pode desabilitar a coleta de telemetria definindo a variável de ambiente <code>DISABLE_TELEMETRY</code> do seu terminal:`,bt,qe,qt="No Linux/MacOS:",Ct,Fe,Et,De,Ft="No Windows:",xt,Ge,Mt,Be,kt,Qe,Tt;return r=new Oe({props:{title:"Instalação",local:"instalação",headingTag:"h1"}}),y=new Oe({props:{title:"Instalação com pip",local:"instalação-com-pip",headingTag:"h2"}}),x=new le({props:{code:"cHl0aG9uJTIwLW0lMjB2ZW52JTIwLmVudg==",highlighted:'python -m venv .<span class="hljs-built_in">env</span>',wrap:!1}}),Q=new le({props:{code:"c291cmNlJTIwLmVudiUyRmJpbiUyRmFjdGl2YXRl",highlighted:'<span class="hljs-built_in">source</span> .<span class="hljs-built_in">env</span>/bin/activate',wrap:!1}}),O=new al({props:{pytorch:!0,tensorflow:!1,jax:!0,$$slots:{jax:[Gl],pytorch:[Fl]},$$scope:{ctx:i}}}),F=new Oe({props:{title:"Instalação a partir do código fonte",local:"instalação-a-partir-do-código-fonte",headingTag:"h2"}}),te=new le({props:{code:"cGlwJTIwaW5zdGFsbCUyMGFjY2VsZXJhdGU=",highlighted:"pip install accelerate",wrap:!1}}),ne=new le({props:{code:"cGlwJTIwaW5zdGFsbCUyMGdpdCUyQmh0dHBzJTNBJTJGJTJGZ2l0aHViLmNvbSUyRmh1Z2dpbmdmYWNlJTJGZGlmZnVzZXJz",highlighted:"pip install git+https://github.com/huggingface/diffusers",wrap:!1}}),re=new Oe({props:{title:"Instalação editável",local:"instalação-editável",headingTag:"h2"}}),Le=new le({props:{code:"Z2l0JTIwY2xvbmUlMjBodHRwcyUzQSUyRiUyRmdpdGh1Yi5jb20lMkZodWdnaW5nZmFjZSUyRmRpZmZ1c2Vycy5naXQlMEFjZCUyMGRpZmZ1c2Vycw==",highlighted:`git <span class="hljs-built_in">clone</span> https://github.com/huggingface/diffusers.git
<span class="hljs-built_in">cd</span> diffusers`,wrap:!1}}),Ee=new al({props:{pytorch:!0,tensorflow:!1,jax:!0,$$slots:{jax:[Yl],pytorch:[Ol]},$$scope:{ctx:i}}}),xe=new fl({props:{warning:!0,$$slots:{default:[Wl]},$$scope:{ctx:i}}}),Je=new le({props:{code:"Y2QlMjB+JTJGZGlmZnVzZXJzJTJGJTBBZ2l0JTIwcHVsbA==",highlighted:`<span class="hljs-built_in">cd</span> ~/diffusers/
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