import{s as tt,o as lt,n as nt}from"../chunks/scheduler.36a0863c.js";import{S as it,i as ot,g as a,s as i,r as c,A as at,h as s,f as l,c as o,j as Ke,u as T,x as r,k as et,y as st,a as n,v as m,d as f,t as d,w as _}from"../chunks/index.9c13489a.js";import{T as rt}from"../chunks/Tip.3b06990e.js";import{C as ee}from"../chunks/CodeBlock.a6a4e7b6.js";import{H as $,E as pt}from"../chunks/index.5de5a341.js";function ct(le){let p,w=`A partire dalla versione 2.3.0 lo script di conversione è parte di transformers CLI (<strong>transformers</strong>), disponibile in ogni installazione
di transformers &gt;=2.3.0.`,h,u,M="La seguente documentazione riflette il formato dei comandi di <strong>transformers convert</strong>.";return{c(){p=a("p"),p.innerHTML=w,h=i(),u=a("p"),u.innerHTML=M},l(J){p=s(J,"P",{"data-svelte-h":!0}),r(p)!=="svelte-61qcrv"&&(p.innerHTML=w),h=o(J),u=s(J,"P",{"data-svelte-h":!0}),r(u)!=="svelte-pgi612"&&(u.innerHTML=M)},m(J,U){n(J,p,U),n(J,h,U),n(J,u,U)},p:nt,d(J){J&&(l(p),l(h),l(u))}}}function Tt(le){let p,w,h,u,M,J,U,je=`È disponibile un’interfaccia a linea di comando per convertire gli originali checkpoint di Bert/GPT/GPT-2/Transformer-XL/XLNet/XLM
in modelli che possono essere caricati utilizzando i metodi <code>from_pretrained</code> della libreria.`,ne,b,ie,v,oe,R,Le=`Puoi convertire qualunque checkpoint Tensorflow di BERT (in particolare
<a href="https://github.com/google-research/bert#pre-trained-models" rel="nofollow">i modeli pre-allenati rilasciati da Google</a>)
in un file di salvataggio Pytorch utilizzando lo script
<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>.`,ae,I,Fe=`Questo CLI prende come input un checkpoint di Tensorflow (tre files che iniziano con <code>bert_model.ckpt</code>) ed il relativo
file di configurazione (<code>bert_config.json</code>), crea un modello Pytorch per questa configurazione, carica i pesi dal
checkpoint di Tensorflow nel modello di Pytorch e salva il modello che ne risulta in un file di salvataggio standard di Pytorch che
può essere importato utilizzando <code>from_pretrained()</code> (vedi l’esempio nel
<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,V,ke=`Devi soltanto lanciare questo script di conversione <strong>una volta</strong> per ottenere un modello Pytorch. Dopodichè, potrai tralasciare
il checkpoint di Tensorflow (i tre files che iniziano con <code>bert_model.ckpt</code>), ma assicurati di tenere il file di configurazione
(<code>bert_config.json</code>) ed il file di vocabolario (<code>vocab.txt</code>) in quanto queste componenti sono necessarie anche per il modello di Pytorch.`,re,E,Ze=`Per lanciare questo specifico script di conversione avrai bisogno di un’installazione di Tensorflow e di Pytorch
(<code>pip install tensorflow</code>). Il resto della repository richiede soltanto Pytorch.`,pe,y,Qe="Questo è un esempio del processo di conversione per un modello <code>BERT-Base Uncased</code> pre-allenato:",ce,g,Te,B,Ae='Puoi scaricare i modelli pre-allenati di Google per la conversione <a href="https://github.com/google-research/bert#pre-trained-models" rel="nofollow">qua</a>.',me,C,fe,P,Ge=`Per il modello ALBERT, converti checkpoint di Tensoflow in Pytorch utilizzando lo script
<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>.`,de,N,He=`Il CLI prende come input un checkpoint di Tensorflow (tre files che iniziano con <code>model.ckpt-best</code>) e i relativi file di
configurazione (<code>albert_config.json</code>), dopodichè crea e salva un modello Pytorch. Per lanciare questa conversione
avrai bisogno di un’installazione di Tensorflow e di Pytorch.`,_e,X,Se="Ecco un esempio del procedimento di conversione di un modello <code>ALBERT Base</code> pre-allenato:",Je,j,ue,L,xe='Puoi scaricare i modelli pre-allenati di Google per la conversione <a href="https://github.com/google-research/albert#pre-trained-models" rel="nofollow">qui</a>.',Ue,F,he,k,Oe=`Ecco un esempio del processo di conversione di un modello OpenAI GPT pre-allenato, assumendo che il tuo checkpoint di NumPy
sia salvato nello stesso formato dei modelli pre-allenati OpenAI (vedi <a href="https://github.com/openai/finetune-transformer-lm" rel="nofollow">qui</a>):`,Me,Z,be,Q,$e,A,We='Ecco un esempio del processo di conversione di un modello OpenAI GPT-2 pre-allenato (vedi <a href="https://github.com/openai/gpt-2" rel="nofollow">qui</a>):',we,G,ve,H,Re,S,De="Ecco un esempio del processo di conversione di un modello XLNet pre-allenato:",Ie,x,Ve,O,Ee,W,ze="Ecco un esempio del processo di conversione di un modello XLM pre-allenato:",ye,D,ge,z,Be,Y,Ye="Ecco un esempio del processo di conversione di un modello T5 pre-allenato:",Ce,q,Pe,K,Ne,te,Xe;return M=new $({props:{title:"Convertire checkpoint di Tensorflow",local:"convertire-checkpoint-di-tensorflow",headingTag:"h1"}}),b=new rt({props:{$$slots:{default:[ct]},$$scope:{ctx:le}}}),v=new $({props:{title:"BERT",local:"bert",headingTag:"h2"}}),g=new ee({props:{code:"ZXhwb3J0JTIwQkVSVF9CQVNFX0RJUiUzRCUyRnBhdGglMkZ0byUyRmJlcnQlMkZ1bmNhc2VkX0wtMTJfSC03NjhfQS0xMiUwQXRyYW5zZm9ybWVycyUyMGNvbnZlcnQlMjAtLW1vZGVsX3R5cGUlMjBiZXJ0JTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0QkVSVF9CQVNFX0RJUiUyRmJlcnRfbW9kZWwuY2twdCUyMCU1QyUwQSUyMCUyMC0tY29uZmlnJTIwJTI0QkVSVF9CQVNFX0RJUiUyRmJlcnRfY29uZmlnLmpzb24lMjAlNUMlMEElMjAlMjAtLXB5dG9yY2hfZHVtcF9vdXRwdXQlMjAlMjRCRVJUX0JBU0VfRElSJTJGcHl0b3JjaF9tb2RlbC5iaW4=",highlighted:`<span class="hljs-built_in">export</span> BERT_BASE_DIR=/path/to/bert/uncased_L-12_H-768_A-12
transformers convert --model_type bert \\
  --tf_checkpoint <span class="hljs-variable">$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 $({props:{title:"ALBERT",local:"albert",headingTag:"h2"}}),j=new ee({props:{code:"ZXhwb3J0JTIwQUxCRVJUX0JBU0VfRElSJTNEJTJGcGF0aCUyRnRvJTJGYWxiZXJ0JTJGYWxiZXJ0X2Jhc2UlMEF0cmFuc2Zvcm1lcnMlMjBjb252ZXJ0JTIwLS1tb2RlbF90eXBlJTIwYWxiZXJ0JTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0QUxCRVJUX0JBU0VfRElSJTJGbW9kZWwuY2twdC1iZXN0JTIwJTVDJTBBJTIwJTIwLS1jb25maWclMjAlMjRBTEJFUlRfQkFTRV9ESVIlMkZhbGJlcnRfY29uZmlnLmpzb24lMjAlNUMlMEElMjAlMjAtLXB5dG9yY2hfZHVtcF9vdXRwdXQlMjAlMjRBTEJFUlRfQkFTRV9ESVIlMkZweXRvcmNoX21vZGVsLmJpbg==",highlighted:`<span class="hljs-built_in">export</span> ALBERT_BASE_DIR=/path/to/albert/albert_base
transformers convert --model_type albert \\
  --tf_checkpoint <span class="hljs-variable">$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}}),F=new $({props:{title:"OpenAI GPT",local:"openai-gpt",headingTag:"h2"}}),Z=new ee({props:{code:"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",highlighted:`<span class="hljs-built_in">export</span> OPENAI_GPT_CHECKPOINT_FOLDER_PATH=/path/to/openai/pretrained/numpy/weights
transformers convert --model_type gpt \\
  --tf_checkpoint <span class="hljs-variable">$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}}),Q=new $({props:{title:"OpenAI GPT-2",local:"openai-gpt-2",headingTag:"h2"}}),G=new ee({props:{code:"ZXhwb3J0JTIwT1BFTkFJX0dQVDJfQ0hFQ0tQT0lOVF9QQVRIJTNEJTJGcGF0aCUyRnRvJTJGb3BlbmFpLWNvbW11bml0eSUyRmdwdDIlMkZwcmV0cmFpbmVkJTJGd2VpZ2h0cyUwQXRyYW5zZm9ybWVycyUyMGNvbnZlcnQlMjAtLW1vZGVsX3R5cGUlMjBncHQyJTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0T1BFTkFJX0dQVDJfQ0hFQ0tQT0lOVF9QQVRIJTIwJTVDJTBBJTIwJTIwLS1weXRvcmNoX2R1bXBfb3V0cHV0JTIwJTI0UFlUT1JDSF9EVU1QX09VVFBVVCUyMCU1QyUwQSUyMCUyMCU1Qi0tY29uZmlnJTIwT1BFTkFJX0dQVDJfQ09ORklHJTVEJTIwJTVDJTBBJTIwJTIwJTVCLS1maW5ldHVuaW5nX3Rhc2tfbmFtZSUyME9QRU5BSV9HUFQyX0ZJTkVUVU5FRF9UQVNLJTVE",highlighted:`<span class="hljs-built_in">export</span> OPENAI_GPT2_CHECKPOINT_PATH=/path/to/openai-community/gpt2/pretrained/weights
transformers convert --model_type gpt2 \\
  --tf_checkpoint <span class="hljs-variable">$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}}),H=new $({props:{title:"XLNet",local:"xlnet",headingTag:"h2"}}),x=new ee({props:{code:"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",highlighted:`<span class="hljs-built_in">export</span> TRANSFO_XL_CHECKPOINT_PATH=/path/to/xlnet/checkpoint
<span class="hljs-built_in">export</span> TRANSFO_XL_CONFIG_PATH=/path/to/xlnet/config
transformers convert --model_type xlnet \\
  --tf_checkpoint <span class="hljs-variable">$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 $({props:{title:"XLM",local:"xlm",headingTag:"h2"}}),D=new ee({props:{code:"ZXhwb3J0JTIwWExNX0NIRUNLUE9JTlRfUEFUSCUzRCUyRnBhdGglMkZ0byUyRnhsbSUyRmNoZWNrcG9pbnQlMEF0cmFuc2Zvcm1lcnMlMjBjb252ZXJ0JTIwLS1tb2RlbF90eXBlJTIweGxtJTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0WExNX0NIRUNLUE9JTlRfUEFUSCUyMCU1QyUwQSUyMCUyMC0tcHl0b3JjaF9kdW1wX291dHB1dCUyMCUyNFBZVE9SQ0hfRFVNUF9PVVRQVVQlMEElMjAlNUItLWNvbmZpZyUyMFhNTF9DT05GSUclNUQlMjAlNUMlMEElMjAlNUItLWZpbmV0dW5pbmdfdGFza19uYW1lJTIwWE1MX0ZJTkVUVU5FRF9UQVNLJTVE",highlighted:`<span class="hljs-built_in">export</span> XLM_CHECKPOINT_PATH=/path/to/xlm/checkpoint
transformers convert --model_type xlm \\
  --tf_checkpoint <span class="hljs-variable">$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}}),z=new $({props:{title:"T5",local:"t5",headingTag:"h2"}}),q=new ee({props:{code:"ZXhwb3J0JTIwVDUlM0QlMkZwYXRoJTJGdG8lMkZ0NSUyRnVuY2FzZWRfTC0xMl9ILTc2OF9BLTEyJTBBdHJhbnNmb3JtZXJzJTIwY29udmVydCUyMC0tbW9kZWxfdHlwZSUyMHQ1JTIwJTVDJTBBJTIwJTIwLS10Zl9jaGVja3BvaW50JTIwJTI0VDUlMkZ0NV9tb2RlbC5ja3B0JTIwJTVDJTBBJTIwJTIwLS1jb25maWclMjAlMjRUNSUyRnQ1X2NvbmZpZy5qc29uJTIwJTVDJTBBJTIwJTIwLS1weXRvcmNoX2R1bXBfb3V0cHV0JTIwJTI0VDUlMkZweXRvcmNoX21vZGVsLmJpbg==",highlighted:`<span class="hljs-built_in">export</span> T5=/path/to/t5/uncased_L-12_H-768_A-12
transformers convert --model_type t5 \\
  --tf_checkpoint <span class="hljs-variable">$T5</span>/t5_model.ckpt \\
  --config <span class="hljs-variable">$T5</span>/t5_config.json \\
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