import{s as tt,o as lt,n as ot}from"../chunks/scheduler.d586627e.js";import{S as nt,i as at,g as r,s as n,r as m,A as rt,h as s,f as l,c as a,j as Ke,u as c,x as p,k as et,y as st,a as o,v as T,d as f,t as d,w as _}from"../chunks/index.8589a59c.js";import{T as pt}from"../chunks/Tip.84e2336e.js";import{C as ee}from"../chunks/CodeBlock.dffc9a5b.js";import{H as $,E as it}from"../chunks/index.0603e7fd.js";function mt(le){let i,w=`A partir da versão 2.3.0 o script de conversão agora faz parte do transformers CLI (<strong>transformers</strong>) disponível em qualquer instalação
transformers &gt;= 2.3.0.`,h,J,M="A documentação abaixo reflete o formato do comando <strong>transformers convert</strong>.";return{c(){i=r("p"),i.innerHTML=w,h=n(),J=r("p"),J.innerHTML=M},l(u){i=s(u,"P",{"data-svelte-h":!0}),p(i)!=="svelte-19hewpm"&&(i.innerHTML=w),h=a(u),J=s(u,"P",{"data-svelte-h":!0}),p(J)!=="svelte-8rjpoy"&&(J.innerHTML=M)},m(u,U){o(u,i,U),o(u,h,U),o(u,J,U)},p:ot,d(u){u&&(l(i),l(h),l(J))}}}function ct(le){let i,w,h,J,M,u,U,Xe=`Uma interface de linha de comando é fornecida para converter os checkpoints originais Bert/GPT/GPT-2/Transformer-XL/XLNet/XLM em modelos
que podem ser carregados usando os métodos <code>from_pretrained</code> da biblioteca.`,oe,b,ne,v,ae,R,Fe=`Você pode converter qualquer checkpoint do BERT em TensorFlow (em particular <a href="https://github.com/google-research/bert#pre-trained-models" rel="nofollow">os modelos pré-treinados lançados pelo Google</a>) em um arquivo PyTorch usando um
<a href="https://github.com/huggingface/transformers/tree/main/src/transformers/models/bert/convert_bert_original_tf_checkpoint_to_pytorch.py" rel="nofollow">convert_bert_original_tf_checkpoint_to_pytorch.py</a> script.`,re,V,Le=`Esta Interface de Linha de Comando (CLI) recebe como entrada um checkpoint do TensorFlow (três arquivos começando com <code>bert_model.ckpt</code>) e o
arquivo de configuração (<code>bert_config.json</code>), e então cria um modelo PyTorch para esta configuração, carrega os pesos
do checkpoint do TensorFlow no modelo PyTorch e salva o modelo resultante em um arquivo PyTorch que pode
ser importado usando <code>from_pretrained()</code> (veja o exemplo em <a href="quicktour">quicktour</a> , <a href="https://github.com/huggingface/transformers/tree/main/examples/pytorch/text-classification/run_glue.py" rel="nofollow">run_glue.py</a> ).`,se,y,Ae=`Você só precisa executar este script de conversão <strong>uma vez</strong> para obter um modelo PyTorch. Você pode então desconsiderar o checkpoint em
TensorFlow (os três arquivos começando com <code>bert_model.ckpt</code>), mas certifique-se de manter o arquivo de configuração (\\
<code>bert_config.json</code>) e o arquivo de vocabulário (<code>vocab.txt</code>), pois eles também são necessários para o modelo PyTorch.`,pe,I,ke="Para executar este script de conversão específico, você precisará ter o TensorFlow e o PyTorch instalados (<code>pip install tensorflow</code>). O resto do repositório requer apenas o PyTorch.",ie,E,Ze="Aqui está um exemplo do processo de conversão para um modelo <code>BERT-Base Uncased</code> pré-treinado:",me,g,ce,B,Qe='Você pode baixar os modelos pré-treinados do Google para a conversão <a href="https://github.com/google-research/bert#pre-trained-models" rel="nofollow">aqui</a>.',Te,C,fe,j,Ge=`Converta os checkpoints do modelo ALBERT em TensorFlow para PyTorch usando o
<a href="https://github.com/huggingface/transformers/tree/main/src/transformers/models/albert/convert_albert_original_tf_checkpoint_to_pytorch.py" rel="nofollow">convert_albert_original_tf_checkpoint_to_pytorch.py</a> script.`,de,N,xe=`A Interface de Linha de Comando (CLI) recebe como entrada um checkpoint do TensorFlow (três arquivos começando com <code>model.ckpt-best</code>) e o
arquivo de configuração (<code>albert_config.json</code>), então cria e salva um modelo PyTorch. Para executar esta conversão, você
precisa ter o TensorFlow e o PyTorch instalados.`,_e,P,He="Aqui está um exemplo do processo de conversão para o modelo <code>ALBERT Base</code> pré-treinado:",ue,X,Je,F,Se='Você pode baixar os modelos pré-treinados do Google para a conversão <a href="https://github.com/google-research/albert#pre-trained-models" rel="nofollow">aqui</a>.',Ue,L,he,A,Oe=`Aqui está um exemplo do processo de conversão para um modelo OpenAI GPT pré-treinado, supondo que seu checkpoint NumPy
foi salvo com o mesmo formato do modelo pré-treinado OpenAI (veja <a href="https://github.com/openai/finetune-transformer-lm" rel="nofollow">aqui</a>\\
)`,Me,k,be,Z,$e,Q,We='Aqui está um exemplo do processo de conversão para um modelo OpenAI GPT-2 pré-treinado (consulte <a href="https://github.com/openai/gpt-2" rel="nofollow">aqui</a>)',we,G,ve,x,Re,H,De="Aqui está um exemplo do processo de conversão para um modelo XLNet pré-treinado:",Ve,S,ye,O,Ie,W,qe="Aqui está um exemplo do processo de conversão para um modelo XLM pré-treinado:",Ee,D,ge,q,Be,Y,Ye="Aqui está um exemplo do processo de conversão para um modelo T5 pré-treinado:",Ce,z,je,K,Ne,te,Pe;return M=new $({props:{title:"Convertendo checkpoints do TensorFlow para Pytorch",local:"convertendo-checkpoints-do-tensorflow-para-pytorch",headingTag:"h1"}}),b=new pt({props:{$$slots:{default:[mt]},$$scope:{ctx:le}}}),v=new $({props:{title:"BERT",local:"bert",headingTag:"h2"}}),g=new ee({props:{code:"ZXhwb3J0JTIwQkVSVF9CQVNFX0RJUiUzRCUyRnBhdGglMkZ0byUyRmJlcnQlMkZ1bmNhc2VkX0wtMTJfSC03NjhfQS0xMiUwQSUwQXRyYW5zZm9ybWVycyUyMGNvbnZlcnQlMjAtLW1vZGVsX3R5cGUlMjBiZXJ0JTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0QkVSVF9CQVNFX0RJUiUyRmJlcnRfbW9kZWwuY2twdCUyMCU1QyUwQSUyMCUyMC0tY29uZmlnJTIwJTI0QkVSVF9CQVNFX0RJUiUyRmJlcnRfY29uZmlnLmpzb24lMjAlNUMlMEElMjAlMjAtLXB5dG9yY2hfZHVtcF9vdXRwdXQlMjAlMjRCRVJUX0JBU0VfRElSJTJGcHl0b3JjaF9tb2RlbC5iaW4=",highlighted:`<span class="hljs-built_in">export</span> BERT_BASE_DIR=/path/to/bert/uncased_L-12_H-768_A-12

transformers convert --model_type bert \\
  --tf_checkpoint <span class="hljs-variable">$BERT_BASE_DIR</span>/bert_model.ckpt \\
  --config <span class="hljs-variable">$BERT_BASE_DIR</span>/bert_config.json \\
  --pytorch_dump_output <span class="hljs-variable">$BERT_BASE_DIR</span>/pytorch_model.bin`,wrap:!1}}),C=new $({props:{title:"ALBERT",local:"albert",headingTag:"h2"}}),X=new ee({props:{code:"ZXhwb3J0JTIwQUxCRVJUX0JBU0VfRElSJTNEJTJGcGF0aCUyRnRvJTJGYWxiZXJ0JTJGYWxiZXJ0X2Jhc2UlMEElMEF0cmFuc2Zvcm1lcnMlMjBjb252ZXJ0JTIwLS1tb2RlbF90eXBlJTIwYWxiZXJ0JTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0QUxCRVJUX0JBU0VfRElSJTJGbW9kZWwuY2twdC1iZXN0JTIwJTVDJTBBJTIwJTIwLS1jb25maWclMjAlMjRBTEJFUlRfQkFTRV9ESVIlMkZhbGJlcnRfY29uZmlnLmpzb24lMjAlNUMlMEElMjAlMjAtLXB5dG9yY2hfZHVtcF9vdXRwdXQlMjAlMjRBTEJFUlRfQkFTRV9ESVIlMkZweXRvcmNoX21vZGVsLmJpbg==",highlighted:`<span class="hljs-built_in">export</span> ALBERT_BASE_DIR=/path/to/albert/albert_base

transformers convert --model_type albert \\
  --tf_checkpoint <span class="hljs-variable">$ALBERT_BASE_DIR</span>/model.ckpt-best \\
  --config <span class="hljs-variable">$ALBERT_BASE_DIR</span>/albert_config.json \\
  --pytorch_dump_output <span class="hljs-variable">$ALBERT_BASE_DIR</span>/pytorch_model.bin`,wrap:!1}}),L=new $({props:{title:"OpenAI GPT",local:"openai-gpt",headingTag:"h2"}}),k=new ee({props:{code:"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",highlighted:`<span class="hljs-built_in">export</span> OPENAI_GPT_CHECKPOINT_FOLDER_PATH=/path/to/openai/pretrained/numpy/weights

transformers convert --model_type gpt \\
  --tf_checkpoint <span class="hljs-variable">$OPENAI_GPT_CHECKPOINT_FOLDER_PATH</span> \\
  --pytorch_dump_output <span class="hljs-variable">$PYTORCH_DUMP_OUTPUT</span> \\
  [--config OPENAI_GPT_CONFIG] \\
  [--finetuning_task_name OPENAI_GPT_FINETUNED_TASK] \\`,wrap:!1}}),Z=new $({props:{title:"OpenAI GPT-2",local:"openai-gpt-2",headingTag:"h2"}}),G=new ee({props:{code:"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",highlighted:`<span class="hljs-built_in">export</span> OPENAI_GPT2_CHECKPOINT_PATH=/path/to/openai-community/gpt2/pretrained/weights

transformers convert --model_type gpt2 \\
  --tf_checkpoint <span class="hljs-variable">$OPENAI_GPT2_CHECKPOINT_PATH</span> \\
  --pytorch_dump_output <span class="hljs-variable">$PYTORCH_DUMP_OUTPUT</span> \\
  [--config OPENAI_GPT2_CONFIG] \\
  [--finetuning_task_name OPENAI_GPT2_FINETUNED_TASK]`,wrap:!1}}),x=new $({props:{title:"XLNet",local:"xlnet",headingTag:"h2"}}),S=new ee({props:{code:"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",highlighted:`<span class="hljs-built_in">export</span> TRANSFO_XL_CHECKPOINT_PATH=/path/to/xlnet/checkpoint
<span class="hljs-built_in">export</span> TRANSFO_XL_CONFIG_PATH=/path/to/xlnet/config

transformers convert --model_type xlnet \\
  --tf_checkpoint <span class="hljs-variable">$TRANSFO_XL_CHECKPOINT_PATH</span> \\
  --config <span class="hljs-variable">$TRANSFO_XL_CONFIG_PATH</span> \\
  --pytorch_dump_output <span class="hljs-variable">$PYTORCH_DUMP_OUTPUT</span> \\
  [--finetuning_task_name XLNET_FINETUNED_TASK] \\`,wrap:!1}}),O=new $({props:{title:"XLM",local:"xlm",headingTag:"h2"}}),D=new ee({props:{code:"ZXhwb3J0JTIwWExNX0NIRUNLUE9JTlRfUEFUSCUzRCUyRnBhdGglMkZ0byUyRnhsbSUyRmNoZWNrcG9pbnQlMEElMEF0cmFuc2Zvcm1lcnMlMjBjb252ZXJ0JTIwLS1tb2RlbF90eXBlJTIweGxtJTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0WExNX0NIRUNLUE9JTlRfUEFUSCUyMCU1QyUwQSUyMCUyMC0tcHl0b3JjaF9kdW1wX291dHB1dCUyMCUyNFBZVE9SQ0hfRFVNUF9PVVRQVVQlMEElMjAlNUItLWNvbmZpZyUyMFhNTF9DT05GSUclNUQlMjAlNUMlMEElMjAlNUItLWZpbmV0dW5pbmdfdGFza19uYW1lJTIwWE1MX0ZJTkVUVU5FRF9UQVNLJTVE",highlighted:`<span class="hljs-built_in">export</span> XLM_CHECKPOINT_PATH=/path/to/xlm/checkpoint

transformers convert --model_type xlm \\
  --tf_checkpoint <span class="hljs-variable">$XLM_CHECKPOINT_PATH</span> \\
  --pytorch_dump_output <span class="hljs-variable">$PYTORCH_DUMP_OUTPUT</span>
 [--config XML_CONFIG] \\
 [--finetuning_task_name XML_FINETUNED_TASK]`,wrap:!1}}),q=new $({props:{title:"T5",local:"t5",headingTag:"h2"}}),z=new ee({props:{code:"ZXhwb3J0JTIwVDUlM0QlMkZwYXRoJTJGdG8lMkZ0NSUyRnVuY2FzZWRfTC0xMl9ILTc2OF9BLTEyJTBBJTBBdHJhbnNmb3JtZXJzJTIwY29udmVydCUyMC0tbW9kZWxfdHlwZSUyMHQ1JTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0VDUlMkZ0NV9tb2RlbC5ja3B0JTIwJTVDJTBBJTIwJTIwLS1jb25maWclMjAlMjRUNSUyRnQ1X2NvbmZpZy5qc29uJTIwJTVDJTBBJTIwJTIwLS1weXRvcmNoX2R1bXBfb3V0cHV0JTIwJTI0VDUlMkZweXRvcmNoX21vZGVsLmJpbg==",highlighted:`<span class="hljs-built_in">export</span> T5=/path/to/t5/uncased_L-12_H-768_A-12

transformers convert --model_type t5 \\
  --tf_checkpoint <span class="hljs-variable">$T5</span>/t5_model.ckpt \\
  --config <span class="hljs-variable">$T5</span>/t5_config.json \\
  --pytorch_dump_output <span class="hljs-variable">$T5</span>/pytorch_model.bin`,wrap:!1}}),K=new 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