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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "3fcd5f6c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting transformers\n",
" Downloading transformers-4.28.1-py3-none-any.whl (7.0 MB)\n",
" ---------------------------------------- 7.0/7.0 MB 722.4 kB/s eta 0:00:00\n",
"Requirement already satisfied: numpy>=1.17 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from transformers) (1.24.3)\n",
"Collecting huggingface-hub<1.0,>=0.11.0\n",
" Downloading huggingface_hub-0.14.1-py3-none-any.whl (224 kB)\n",
" ------------------------------------ 224.5/224.5 kB 762.4 kB/s eta 0:00:00\n",
"Requirement already satisfied: pyyaml>=5.1 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from transformers) (6.0)\n",
"Requirement already satisfied: filelock in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from transformers) (3.12.0)\n",
"Requirement already satisfied: packaging>=20.0 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from transformers) (21.3)\n",
"Requirement already satisfied: regex!=2019.12.17 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from transformers) (2022.7.9)\n",
"Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
" Downloading tokenizers-0.13.3-cp39-cp39-win_amd64.whl (3.5 MB)\n",
" ---------------------------------------- 3.5/3.5 MB 738.0 kB/s eta 0:00:00\n",
"Requirement already satisfied: tqdm>=4.27 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from transformers) (4.64.1)\n",
"Requirement already satisfied: requests in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from transformers) (2.28.1)\n",
"Requirement already satisfied: fsspec in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (2022.7.1)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (4.3.0)\n",
"Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from packaging>=20.0->transformers) (3.0.9)\n",
"Requirement already satisfied: colorama in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from tqdm>=4.27->transformers) (0.4.5)\n",
"Requirement already satisfied: idna<4,>=2.5 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from requests->transformers) (3.3)\n",
"Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from requests->transformers) (2022.12.7)\n",
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from requests->transformers) (1.26.11)\n",
"Requirement already satisfied: charset-normalizer<3,>=2 in c:\\users\\atharva\\anaconda3\\lib\\site-packages (from requests->transformers) (2.0.4)\n",
"Installing collected packages: tokenizers, huggingface-hub, transformers\n",
"Successfully installed huggingface-hub-0.14.1 tokenizers-0.13.3 transformers-4.28.1\n"
]
}
],
"source": [
"!pip install transformers"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "9b7e3e88",
"metadata": {},
"outputs": [],
"source": [
"from transformers import pipeline"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bf785b14",
"metadata": {},
"outputs": [],
"source": [
"##BART -LARGE-MNLI"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "ac57b4d0",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"classifier_pipeline=pipeline(\"zero-shot-classification\",model=\"facebook/bart-large-mnli\",)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "8b1d9736",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'sequence': 'I love travelling',\n",
" 'labels': ['travelling', 'entertainment', 'technology', 'dancing', 'cooking'],\n",
" 'scores': [0.930633544921875,\n",
" 0.057743728160858154,\n",
" 0.004555718973278999,\n",
" 0.004288351628929377,\n",
" 0.0027786651626229286]}"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"input_sequences=\"I love travelling\"\n",
"label_candidates=[\"travelling\",\"cooking\",\"entertainment\",\"dancing\",\"technology\"]\n",
"classifier_pipeline(input_sequences,label_candidates)\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "80d56ec0",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"import pickle\n",
"pickle_out=open(\"classfier_pipeline.pkl\",\"wb\")\n",
"pickle.dump=(classifier_pipeline,pickle_out)\n",
"pickle_out.close()\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "19f74f84",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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