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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## tokenizer\n",
"\n",
"tokenizer负责将输入的字符串，转换为token，或者转换为ids序列"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# 导入模型\n",
"from transformers import AutoTokenizer\n",
"tokenizer = AutoTokenizer.from_pretrained(\"liam168/c2-roberta-base-finetuned-dianping-chinese\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['这', '是', '中', '英', '文', 'test', '语', '句', '，', 'mix', '中', '英', '文', '及', '标', '点', '符', '号']\n",
"['测', '试', 'mix', '中', '英', '文', '及', '标', '点', '符', '号']\n"
]
}
],
"source": [
"# 转换为token\n",
"input = \"这是中英文test语句，mix中英文及标点符号\"\n",
"input_array = [\"测试\",\"mix中英文及标点符号\"]\n",
"print(tokenizer.tokenize(input))\n",
"print(tokenizer.tokenize(input_array))\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([[ 101, 6821, 3221, 704, 5739, 3152, 10060, 6427, 1368, 8024,\n",
" 9678, 704, 5739, 3152, 1350, 3403, 4157, 5016, 1384, 102]])\n",
"tensor([[ 101, 3844, 6407, 102, 9678, 704, 5739, 3152, 1350, 3403, 4157, 5016,\n",
" 1384, 102]])\n",
"['[CLS]', '这', '是', '中', '英', '文', 'test', '语', '句', '，', 'mix', '中', '英', '文', '及', '标', '点', '符', '号', '[SEP]']\n",
"['[CLS]', '测', '试', '[SEP]', 'mix', '中', '英', '文', '及', '标', '点', '符', '号', '[SEP]']\n"
]
}
],
"source": [
"#转换为id序列\n",
"ids = tokenizer(input,padding=True,truncation=True,max_length=512,return_tensors=\"pt\")\n",
"print(ids.input_ids)\n",
"idss = tokenizer([input_array],padding=True,truncation=True,max_length=512,return_tensors=\"pt\")\n",
"print(idss.input_ids)\n",
"\n",
"#将ids序列，又解码成为token\n",
"print(tokenizer.convert_ids_to_tokens(ids.input_ids[0]))\n",
"print(tokenizer.convert_ids_to_tokens(idss.input_ids[0]))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
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"version": "3.8.10"
},
"orig_nbformat": 4,
"vscode": {
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