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"StyleView", "description_width": "" } } } } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "source": [ "# 1. Dataset Preparation" ], "metadata": { "id": "LNsZ3c69cGnY" } }, { "cell_type": "code", "source": [ "!nvidia-smi " ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Loz2U2x_xxpj", "outputId": "e550a634-f73e-420a-d281-6a775f77099b" }, "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Mon Jun 5 04:18:42 2023 \n", "+-----------------------------------------------------------------------------+\n", "| NVIDIA-SMI 525.85.12 Driver Version: 525.85.12 CUDA Version: 12.0 |\n", "|-------------------------------+----------------------+----------------------+\n", "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", "| | | MIG M. |\n", "|===============================+======================+======================|\n", "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", "| N/A 62C P8 11W / 70W | 0MiB / 15360MiB | 0% Default |\n", "| | | N/A |\n", "+-------------------------------+----------------------+----------------------+\n", " \n", "+-----------------------------------------------------------------------------+\n", "| Processes: |\n", "| GPU GI CI PID Type Process name GPU Memory |\n", "| ID ID Usage |\n", "|=============================================================================|\n", "| No running processes found |\n", "+-----------------------------------------------------------------------------+\n" ] } ] }, { "cell_type": "code", "source": [ "!pip install datasets" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "oAkWgqvwc34x", "outputId": "925b0b15-e1c2-4ee3-9776-97b8b8aa7cc4" }, "execution_count": 2, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting datasets\n", " Downloading datasets-2.12.0-py3-none-any.whl (474 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m474.6/474.6 kB\u001b[0m \u001b[31m39.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.22.4)\n", "Requirement already satisfied: pyarrow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (9.0.0)\n", "Collecting dill<0.3.7,>=0.3.0 (from datasets)\n", " Downloading dill-0.3.6-py3-none-any.whl (110 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m110.5/110.5 kB\u001b[0m \u001b[31m16.5 MB/s\u001b[0m eta 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installed aiohttp-3.8.4 aiosignal-1.3.1 async-timeout-4.0.2 datasets-2.12.0 dill-0.3.6 frozenlist-1.3.3 huggingface-hub-0.15.1 multidict-6.0.4 multiprocess-0.70.14 responses-0.18.0 xxhash-3.2.0 yarl-1.9.2\n" ] } ] }, { "cell_type": "code", "source": [ "from datasets import load_dataset\n", "dataset = load_dataset(\"stsb_multi_mt\", name=\"en\", split=\"train\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 296, "referenced_widgets": [ "af1447d9bcdf4aca9565b6fc6ea1925e", "3d8d2fb343a247c8a18261296d853ada", "99ba3022e3ce4c8a951f10def140926a", "e641966dcabb4b8a9b4cdf6e8119cb01", "e29c844f5c71456bbeee66ee6dd04e9f", "e264fde939754c2f99505ecbfc772ac2", "0a70b07df2e44c1585d50b0dfaa75c1c", "2a58190009a54fb39724ae91dd2a03c3", "3b6a9922fbc94db5bee56ab828c4c72f", "722c285950d0449ea0d91617210a72a9", "e33ad31d5b264705bd2be4e217381e0d", "643fa374d2604c3cbb2d64a6f521dd85", "a17a23a19dc44a54aafc75e8f43b5384", "17e54f01287e4ff2bab5067a8bcc88c9", 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"334642a1c7ee4698ae986935293aa717", "39042492cd9b49d695621b09da8d3708", "2d5bca69411c4ec9b2bc8cb2f02408f1", "12c547c644b94badb5ae5848f26d13d6", "ff0e5e91effe463a932914804f4a2937", "17a58c9332e94970b32126408bb4c57c", "75dcc03186d44fd0b545e36fbef66634", "49d653001d604910a37232d4d2d5a56b", "76858b7ed6be417ab82339fd7cd5de9f", "a05efa676adf4139924970ce8d310cfb", "5268ced2d4484a448c2583d07008d57a", "f9fda21c00de4ee09ff71cfef614b0b0", "6d0aea40fac14c239a1c19edafea8455", "32e6a4fb67f843da8658ac0542a90539", "2bd2fafe92584bfcb57843683d902bc1" ] }, "id": "ZyYsS2AccZ2u", "outputId": "2a70ff74-d209-4cd6-fc44-68f4822f002b" }, "execution_count": 3, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading builder script: 0%| | 0.00/7.43k [00:00\n", "
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sentence1sentence2similarity_score
0A plane is taking off.An air plane is taking off.5.00
1A man is playing a large flute.A man is playing a flute.3.80
2A man is spreading shreded cheese on a pizza.A man is spreading shredded cheese on an uncoo...3.80
3Three men are playing chess.Two men are playing chess.2.60
4A man is playing the cello.A man seated is playing the cello.4.25
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sentence1sentence2score
0A plane is taking off.An air plane is taking off.5.000
1A man is playing a large flute.A man is playing a flute.3.800
2A man is spreading shreded cheese on a pizza.A man is spreading shredded cheese on an uncoo...3.800
3Three men are playing chess.Two men are playing chess.2.600
4A man is playing the cello.A man seated is playing the cello.4.250
5Some men are fighting.Two men are fighting.4.250
6A man is smoking.A man is skating.0.500
7The man is playing the piano.The man is playing the guitar.1.600
8A man is playing on a guitar and singing.A woman is playing an acoustic guitar and sing...2.200
9A person is throwing a cat on to the ceiling.A person throws a cat on the ceiling.5.000
10The man hit the other man with a stick.The man spanked the other man with a stick.4.200
11A woman picks up and holds a baby kangaroo.A woman picks up and holds a baby kangaroo in ...4.600
12A man is playing a flute.A man is playing a bamboo flute.3.867
13A person is folding a piece of paper.Someone is folding a piece of paper.4.667
14A man is running on the road.A panda dog is running on the road.1.667
15A dog is trying to get bacon off his back.A dog is trying to eat the bacon on its back.3.750
16The polar bear is sliding on the snow.A polar bear is sliding across the snow.5.000
17A woman is writing.A woman is swimming.0.500
18A cat is rubbing against baby's face.A cat is rubbing against a baby.3.800
19The man is riding a horse.A man is riding on a horse.5.000
20A man pours oil into a pot.A man pours wine in a pot.3.200
21A man is playing a guitar.A girl is playing a guitar.2.800
22A panda is sliding down a slide.A panda slides down a slide.4.600
23A woman is eating something.A woman is eating meat.3.000
24A woman peels a potato.A woman is peeling a potato.5.000
25The boy fell off his bike.A boy falls off his bike.4.800
26The woman is playing the flute.A woman is playing a flute.5.000
27A rabbit is running from an eagle.A hare is running from a eagle.4.200
28The woman is frying a breaded pork chop.A woman is cooking a breaded pork chop.4.200
29A girl is flying a kite.A girl running is flying a kite.4.000
30A man is riding a mechanical bull.A man rode a mechanical bull.4.000
31The man is playing the guitar.A man is playing a guitar.4.909
32A woman is dancing and singing with other women.A woman is dancing and singing in the rain.3.000
33A man is slicing a bun.A man is slicing an onion.2.400
34A man is pouring oil into a pan.A man is pouring oil into a skillet.4.200
35A lion is playing with people.A lion is playing with two men.3.400
36A dog rides a skateboard.A dog is riding a skateboard.5.000
37Someone is carving a statue.A man is carving a statue.3.750
38A woman is slicing an onion.A man is cutting an onion.2.750
39A woman peels shrimp.A woman is peeling shrimp.5.000
40A woman is frying fish.A woman is cooking fish.4.000
41A woman is playing an electric guitar.A woman is playing a guitar.3.600
42A baby tiger is playing with a ball.A baby is playing with a doll.1.600
43A person is slicing a tomato.A person is slicing some meat.1.750
44A person cuts an onion.A person is cutting an onion.5.000
45A man is playing the piano.A woman is playing the violin.1.000
46A woman is playing the flute.A man is playing the guitar.1.000
47A man is cutting up a potato.A man is cutting up carrots.2.375
48A kid is playing guitar.A boy is playing a guitar.3.800
49A boy is playing guitar.A man is playing a guitar.3.200
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\n", " " ] }, "metadata": {}, "execution_count": 8 } ] }, { "cell_type": "markdown", "source": [ "## 1.1 Getting translator to translate english sentences into nepali" ], "metadata": { "id": "d7ThAP8_c_CT" } }, { "cell_type": "code", "source": [ "!pip install deep-translator" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "wPI57eArdvHI", "outputId": "2da908a3-ca74-445a-c2f0-fb8e31035307" }, "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting deep-translator\n", " Downloading deep_translator-1.11.1-py3-none-any.whl (37 kB)\n", "Requirement already satisfied: beautifulsoup4<5.0.0,>=4.9.1 in /usr/local/lib/python3.10/dist-packages (from deep-translator) (4.11.2)\n", "Requirement already satisfied: requests<3.0.0,>=2.23.0 in /usr/local/lib/python3.10/dist-packages (from deep-translator) (2.27.1)\n", "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4<5.0.0,>=4.9.1->deep-translator) (2.4.1)\n", "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.23.0->deep-translator) (1.26.15)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.23.0->deep-translator) (2022.12.7)\n", "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.23.0->deep-translator) (2.0.12)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.23.0->deep-translator) (3.4)\n", "Installing collected packages: deep-translator\n", "Successfully installed deep-translator-1.11.1\n" ] } ] }, { "cell_type": "code", "source": [ "from deep_translator import GoogleTranslator \n", "from tqdm import tqdm" ], "metadata": { "id": "NMivpnstdzDf" }, "execution_count": 10, "outputs": [] }, { "cell_type": "code", "source": [ "text = df['sentence2'][100]\n", "\n", "translated = GoogleTranslator(source=\"auto\", target=\"ne\").translate(text)\n", "print(translated)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "HwJppundpnZ-", "outputId": "fb79d275-8f8e-413e-ed42-552b509dc016" }, "execution_count": 11, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "कोही गितार बजाइरहेका छन्।\n" ] } ] }, { "cell_type": "code", "source": [ "def translate_text(text, target_lang):\n", " translator = GoogleTranslator(source=\"auto\", target=target_lang)\n", " translation = translator.translate(text)\n", "\n", " return translation\n", "\n", "\n", "target_lang = \"ne\"\n", "columns_to_translate = [\"sentence1\", \"sentence2\"]\n", "\n", "for column in columns_to_translate:\n", " tqdm.pandas(desc=f\"Translating {column}\")\n", " df[column] = df[column].progress_apply(lambda x: translate_text(x, target_lang))\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "RYYa17PEfliw", "outputId": "a84f2a94-d602-42f5-b237-cda87e9bdd17" }, "execution_count": 12, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "Translating sentence1: 100%|██████████| 5749/5749 [20:59<00:00, 4.56it/s]\n", "Translating sentence2: 100%|██████████| 5749/5749 [20:18<00:00, 4.72it/s]\n" ] } ] }, { "cell_type": "code", "source": [ "from google.colab import drive\n", "drive.mount('/content/drive')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "LVT8wvq5Ssal", "outputId": "9ff4d321-189e-4310-c690-429780078c88" }, "execution_count": 13, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Mounted at /content/drive\n" ] } ] }, { "cell_type": "code", "source": [ "# import pandas as pd\n", "\n", "\n", "# csv_path = '/content/drive/My Drive/Datasets/stsb_multi_mt_nepali_cleaned.csv'\n", "# df = pd.read_csv(csv_path)" ], "metadata": { "id": "kK0a63FHS1pW" }, "execution_count": 14, "outputs": [] }, { "cell_type": "code", "source": [ "df.head(100)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 424 }, "id": "FCrVcMuXip-O", "outputId": "b4542263-1ce2-478d-fc21-ed85f5c5bffc" }, "execution_count": 14, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " sentence1 \\\n", "0 एउटा विमान उडिरहेको छ। \n", "1 एउटा मान्छे ठूलो बाँसुरी बजाइरहेको छ। \n", "2 एक व्यक्ति पिज्जामा टुक्रा चिज फैलाउँदै छ। \n", "3 तीन जना चेस खेल्दै छन्। \n", "4 एउटा मान्छे सेलो बजाउँदै छ। \n", ".. ... \n", "95 दुई जना केटाले गाडी चलाइरहेका छन् । \n", "96 एउटा मानिस घोडामा सवार छ। \n", "97 एकजना मानिस साइकल चलाइरहेका छन्। \n", "98 एउटा मान्छे आलु काट्दै छ। \n", "99 एउटी महिला आलु बोक्दै छिन्। \n", "\n", " sentence2 score \n", "0 हवाई जहाज उडिरहेको छ। 5.00 \n", "1 एउटा मान्छे बाँसुरी बजाउँदै छ। 3.80 \n", "2 एक जना मानिसले न पकाएको पिज्जामा टुक्रा पारेको... 3.80 \n", "3 दुई जना पुरुष चेस खेलिरहेका छन्। 2.60 \n", "4 बसेको मान्छे सेलो खेलिरहेको छ। 4.25 \n", ".. ... ... \n", "95 दुई खाडीहरू नाचिरहेका छन्। 0.60 \n", "96 एउटी केटी घोडा चढ्दै छिन्। 2.60 \n", "97 बाँदर बाइक चलाउँदै छ। 2.00 \n", "98 एउटी महिला आलु बोक्दै छिन्। 2.20 \n", "99 एउटा मान्छे आलु काट्दै छ। 2.40 \n", "\n", "[100 rows x 3 columns]" ], "text/html": [ "\n", "
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sentence1sentence2score
0एउटा विमान उडिरहेको छ।हवाई जहाज उडिरहेको छ।5.00
1एउटा मान्छे ठूलो बाँसुरी बजाइरहेको छ।एउटा मान्छे बाँसुरी बजाउँदै छ।3.80
2एक व्यक्ति पिज्जामा टुक्रा चिज फैलाउँदै छ।एक जना मानिसले न पकाएको पिज्जामा टुक्रा पारेको...3.80
3तीन जना चेस खेल्दै छन्।दुई जना पुरुष चेस खेलिरहेका छन्।2.60
4एउटा मान्छे सेलो बजाउँदै छ।बसेको मान्छे सेलो खेलिरहेको छ।4.25
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95दुई जना केटाले गाडी चलाइरहेका छन् ।दुई खाडीहरू नाचिरहेका छन्।0.60
96एउटा मानिस घोडामा सवार छ।एउटी केटी घोडा चढ्दै छिन्।2.60
97एकजना मानिस साइकल चलाइरहेका छन्।बाँदर बाइक चलाउँदै छ।2.00
98एउटा मान्छे आलु काट्दै छ।एउटी महिला आलु बोक्दै छिन्।2.20
99एउटी महिला आलु बोक्दै छिन्।एउटा मान्छे आलु काट्दै छ।2.40
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\n", " " ] }, "metadata": {}, "execution_count": 14 } ] }, { "cell_type": "code", "source": [ "df.to_csv('stsb_multi_mt_nepali.csv', index=False)" ], "metadata": { "id": "eBWzpbhV4Bpx" }, "execution_count": 15, "outputs": [] }, { "cell_type": "markdown", "source": [ "\n", "## 1.2 Removing alphabets \n" ], "metadata": { "id": "BFvBWyvU4g-G" } }, { "cell_type": "code", "source": [ "import re\n", "\n", "def remove_alphabets(text):\n", " if isinstance(text, str):\n", " pattern = r'[a-zA-Z]'\n", " return re.sub(pattern, '', text)\n", " else:\n", " return text\n", "\n", "df = df.applymap(remove_alphabets)" ], "metadata": { "id": "xEL7Jx7Q6bPk" }, "execution_count": 16, "outputs": [] }, { "cell_type": "code", "source": [ "df.iloc[843]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "gCKIdgj_61a-", "outputId": "d3b803c8-bbf4-4dc1-afc3-e6b36aa6c833" }, "execution_count": 17, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "sentence1 केटीहरू स्टेजमा हिँडिरहेका छन्।\n", "sentence2 महिला मोडलहरू क्याटवाक गर्दै छन्।\n", "score 2.6\n", "Name: 843, dtype: object" ] }, "metadata": {}, "execution_count": 17 } ] }, { "cell_type": "code", "source": [ "df.to_csv('stsb_multi_mt_nepali_cleaned.csv', index=False)" ], "metadata": { "id": "Y2-sWE7F7TZA" }, "execution_count": 18, "outputs": [] }, { "cell_type": "markdown", "source": [ "# 2. Training Sentence Transformer" ], "metadata": { "id": "Ke9ieYET8SgR" } }, { "cell_type": "code", "source": [ "!pip install sentence_transformers" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "qVWtQfPL83WO", "outputId": "e5828243-1fd3-4ef9-87d3-50147c5499ae" }, "execution_count": 19, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting sentence_transformers\n", " Downloading sentence-transformers-2.2.2.tar.gz (85 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m86.0/86.0 kB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "Collecting transformers<5.0.0,>=4.6.0 (from sentence_transformers)\n", " Downloading transformers-4.29.2-py3-none-any.whl (7.1 MB)\n", "\u001b[2K 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tokenizers, sentencepiece, transformers, sentence_transformers\n", "Successfully installed sentence_transformers-2.2.2 sentencepiece-0.1.99 tokenizers-0.13.3 transformers-4.29.2\n" ] } ] }, { "cell_type": "code", "source": [ "import torch\n", "from torch.utils.data import DataLoader\n", "import math\n", "from sentence_transformers import SentenceTransformer, LoggingHandler, losses, models, util\n", "from sentence_transformers.evaluation import EmbeddingSimilarityEvaluator\n", "from sentence_transformers.readers import InputExample\n", "import logging\n", "from datetime import datetime" ], "metadata": { "id": "BXROqyqO822p" }, "execution_count": 20, "outputs": [] }, { "cell_type": "code", "source": [ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", "device" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "TNA_j5t7QrTg", "outputId": "54d86822-b2aa-4915-8adf-2dcb6833b7f8" }, "execution_count": 21, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "device(type='cuda')" ] }, "metadata": {}, "execution_count": 21 } ] }, { "cell_type": "code", "source": [ "model_name = 'Rajan/NepaliBERT'\n", "\n", "train_batch_size = 16\n", "num_epochs = 8\n", "model_save_path = 'output/sentence_transformer_nepali'" ], "metadata": { "id": "rNd6o8Su73Lm" }, "execution_count": 22, "outputs": [] }, { "cell_type": "code", "source": [ "word_embedding_model = models.Transformer(model_name)\n", "pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension(), \n", " pooling_mode_mean_tokens=True,\n", " pooling_mode_cls_token=False,\n", " pooling_mode_max_tokens=False,\n", " )" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 220, "referenced_widgets": [ "be5105b59501495e8e11da141dbcf5e7", "fefb28c113ef411caa85b6d98b5f1d44", "3adae3710e904be28dc5781f9a9bd7d5", "e837a91fd05d48e792b0f7aafbdab56e", "82ce6784a8cb4f1da7055fffd7e30929", "73f717b3a2674f2a8ef2a77159d494f7", "e0b8db4c977a4c3189ba023718834950", "d0a13aaf2d6041258b9b09af2cc685fa", "e0d30c3acc834e458271d09f1822a12f", "fd66352294854b869f0aea89e36969ee", "975dc7745a2847c390fbc632e728c8cc", "41419856109b49758f9182af84dd5e69", "bc0abb14352a4eccb2088764b1c0b648", "5edd89f93fa2437fa10c15b85f87885d", "468c63ccd9534db2a5bee49d8b363cd5", "bd932ea2c57c4c46b22f1ec6f7fd0179", "a5b756cfc21d4e06b4f5b2596b887f4d", "cad631f60d674ed99f28ebda0ac39266", "74b2406ae1b44a5ea6846fe57e1a2b4c", "414c3a8e9c444e50ab2c921d2777f441", "4bd8f08cc1c5442eac9967dbfcba7c1b", "2bb75616894141eaaf40e91732fc44ed", "8d3aafb4e6bd48c4b18064f509099084", "ee108dcd2d544d8093b337e2472fd350", "c9fcc7cadca84507a44b29a83fdd0db7", "c5e1cf2e61c54e28acf859c3be2bb1d0", "d3ed57a171c648bebc0d01b3fc941b7a", "0161f515eca1422cb77d4e81ca8091bf", "84cf8341d6264076920ad234db39942d", "5749674902734511a5c24264c4669ffb", "5f036807a1d14782bc4df29074809fcb", "81e8a232673047fba152e92876834337", "b987e739fb33419fa580cf36430b57fd" ] }, "id": "zHF933dR8fPl", "outputId": "87eb198e-0457-455f-971e-9fdf2a782b8a" }, "execution_count": 23, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)lve/main/config.json: 0%| | 0.00/569 [00:00=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.65.0)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (6.0)\n", "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.5.0)\n", "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (23.1)\n", "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (1.26.15)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2022.12.7)\n", "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2.0.12)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.4)\n" ] } ] }, { "cell_type": "code", "source": [ "!huggingface-cli login" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "GtfRTEd8bmA0", "outputId": "001372b6-6d17-480b-e755-df15c5027e47" }, "execution_count": 34, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", " _| _| _| _| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _|_|_|_| _|_| _|_|_| _|_|_|_|\n", " _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|\n", " _|_|_|_| _| _| _| _|_| _| _|_| _| _| _| _| _| _|_| _|_|_| _|_|_|_| _| _|_|_|\n", " _| _| _| _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|\n", " _| _| _|_| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _| _| _| _|_|_| _|_|_|_|\n", " \n", " To login, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n", "Token: \n", "Add token as git credential? (Y/n) n\n", "Token is valid (permission: write).\n", "Your token has been saved to /root/.cache/huggingface/token\n", "Login successful\n" ] } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import notebook_login\n", "\n", "notebook_login()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 113, "referenced_widgets": [ "d07442f23eeb410e8d3a30679ab9ba67", "5ade347aacc44287a6405dbc223aa039", "3591cb3458cc44faa0d2a3a6a56d29ab", "47b9c728eb2d45c68f95b1194fb91728", "f8ca30bd31024919ac8624d29e7bb3af", "eb65315d0ee64335a8d4547797343442", "4472151a14af46a4895a9785793b6f4d", "57158e0cbf6945b88418c7a91dbf94f1", "e77bcc3d704549ee907745263662d08c", "1c317f137a99421b92001873c79f99ed", "447e3c2b55214ed98a235a96e67957c7", "7fd9f24a83884c07ad271c8c5560a0f7", "36848ef5ef3d452398d342a67c0fbb47", "dc3baed25d764f3f918431aa1170ef3e", "c53adf48e900455e9c7a96ef8adbf8ee", "b9019c02aea0488dae0ae32ba8023314", "3cddd3c46af9445e952cead6dc216ff2", "e536f56a9231454e83829f0296c9be1a", "4f6a3f987bb047cfaf4bb424c008db1c", "6520bc57a6a74753a94c94df2215f0f9", "99201aae69284ec3a0c476d9d516d83c", "2538b7513c54460fbebfebc45ecd561a", "db20f856f47d4924bbd5347d4c67ab84", "538e28f9eda64fe791e20a72dc668464", "042695bad4454748b43e7776f5c2f536", "b492ea832c724f3dbbaed096ef65fa9e", "319c0d91e081487db3e64e7791935327", "9a956d7c25624eb3ae875778f7e7d5db", "e395497b95fe4ee5b9d61628373bfbbb" ] }, "id": "ROvh_efWULHV", "outputId": "e1663053-3526-4b70-f6c2-6f24a6f7d47a" }, "execution_count": 35, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='