{
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   "id": "a59aaa09",
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   "outputs": [
    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dd105016112541b194045b128689cfe5",
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       "model.safetensors:   0%|          | 0.00/445M [00:00<?, ?B/s]"
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     },
     "metadata": {},
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    },
    {
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     "text": [
      "Some weights of the model checkpoint at camembert-base were not used when initializing CamembertForMaskedLM: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n",
      "- This IS expected if you are initializing CamembertForMaskedLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing CamembertForMaskedLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
     ]
    },
    {
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       "tokenizer_config.json:   0%|          | 0.00/25.0 [00:00<?, ?B/s]"
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       "sentencepiece.bpe.model:   0%|          | 0.00/811k [00:00<?, ?B/s]"
      ]
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    {
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      "text/plain": [
       "tokenizer.json:   0%|          | 0.00/1.40M [00:00<?, ?B/s]"
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     },
     "metadata": {},
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    },
    {
     "data": {
      "text/plain": [
       "('./tokenizer_config.json',\n",
       " './special_tokens_map.json',\n",
       " './sentencepiece.bpe.model',\n",
       " './added_tokens.json',\n",
       " './tokenizer.json')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from transformers import AutoModelForMaskedLM, AutoTokenizer\n",
    "\n",
    "checkpoint = \"camembert-base\"\n",
    "\n",
    "model = AutoModelForMaskedLM.from_pretrained(checkpoint)\n",
    "tokenizer = AutoTokenizer.from_pretrained(checkpoint)\n",
    "\n",
    "\n",
    "model.save_pretrained(\".\")\n",
    "tokenizer.save_pretrained(\".\")"
   ]
  }
 ],
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