KoSentenceBERT-SKT

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Sentence Embeddings using Siamese SKT KoBERT

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Download Latest Version (.zip)

- - multinli.train.ko.tsv
  - snli_1.0_train.ko.tsv
  - xnli.dev.ko.tsv
  - xnli.test.ko.tsv
- - sts-dev.tsv
  - sts-test.tsv
  - sts-train.tsv
  - tune_dev.tsv
  - tune_test.tsv
  - tune_train.tsv
- LICENSE
- README.md
- - config.json
  - modules.json
- - config.json
  - modules.json
- - config.json
  - modules.json
- - __init__.py
  - EncodeDataset.py
  - ParallelSentencesDataset.py
  - SentenceLabelDataset.py
  - SentencesDataset.py
- - __init__.py
  - BinaryClassificationEvaluator.py
  - EmbeddingSimilarityEvaluator.py
  - InformationRetrievalEvaluator.py
  - LabelAccuracyEvaluator.py
  - MSEEvaluator.py
  - MSEEvaluatorFromDataFrame.py
  - ParaphraseMiningEvaluator.py
  - SentenceEvaluator.py
  - SequentialEvaluator.py
  - SimilarityFunction.py
  - TranslationEvaluator.py
  - TripletEvaluator.py
- - __init__.py
  - BatchAllTripletLoss.py
  - BatchHardSoftMarginTripletLoss.py
  - BatchHardTripletLoss.py
  - BatchSemiHardTripletLoss.py
  - ContrastiveLoss.py
  - CosineSimilarityLoss.py
  - MSELoss.py
  - MultipleNegativesRankingLoss.py
  - OnlineContrastiveLoss.py
  - SoftmaxLoss.py
  - TripletLoss.py
- - __init__.py
  - ALBERT.py
  - BERT.py
  - BoW.py
  - CamemBERT.py
  - CNN.py
  - Dense.py
  - DistilBERT.py
  - LASER.py
  - LSTM.py
  - Pooling.py
  - RoBERTa.py
  - T5.py
  - Transformer.py
  - WeightedLayerPooling.py
  - WKPooling.py
  - WordEmbeddings.py
  - WordWeights.py
  - XLMRoBERTa.py
  - XLNet.py
- - __init__.py
  - InputExample.py
  - LabelSentenceReader.py
  - NLIDataReader.py
  - PairedFilesReader.py
  - STSDataReader.py
  - TripletReader.py
- __init__.py
- LoggingHandler.py
- SentenceTransformer.py
- util.py
- - __init__.py
  - __init__.pyi
- - __init__.py
  - base_tokenizer.py
  - bert_wordpiece.py
  - byte_level_bpe.py
  - char_level_bpe.py
  - sentencepiece_bpe.py
- - __init__.py
  - __init__.pyi
- - __init__.py
  - __init__.pyi
- - __init__.py
  - __init__.pyi
- - __init__.py
  - __init__.pyi
- - __init__.py
  - __init__.pyi
- __init__.py
- __init__.pyi
- tokenizers.cpython-35m-x86_64-linux-gnu.so
- tokenizers.cpython-36m-x86_64-linux-gnu.so
- tokenizers.cpython-37m-x86_64-linux-gnu.so
- - __init__.py
  - convert.py
  - download.py
  - env.py
  - run.py
  - serving.py
  - train.py
  - user.py
- - __init__.py
- __init__.py
- __main__.py
- activations.py
- another_try.py
- benchmark_utils.py
- configuration_albert.py
- configuration_auto.py
- configuration_bart.py
- configuration_bert.py
- configuration_camembert.py
- configuration_ctrl.py
- configuration_distilbert.py
- configuration_electra.py
- configuration_flaubert.py
- configuration_gpt2.py
- configuration_mmbt.py
- configuration_openai.py
- configuration_roberta.py
- configuration_t5.py
- configuration_transfo_xl.py
- configuration_utils.py
- configuration_xlm.py
- configuration_xlm_roberta.py
- configuration_xlnet.py
- convert_albert_original_tf_checkpoint_to_pytorch.py
- convert_bart_original_pytorch_checkpoint_to_pytorch.py
- convert_bert_original_tf_checkpoint_to_pytorch.py
- convert_bert_pytorch_checkpoint_to_original_tf.py
- convert_dialogpt_original_pytorch_checkpoint_to_pytorch.py
- convert_electra_original_tf_checkpoint_to_pytorch.py
- convert_gpt2_original_tf_checkpoint_to_pytorch.py
- convert_openai_original_tf_checkpoint_to_pytorch.py
- convert_pytorch_checkpoint_to_tf2.py
- convert_roberta_original_pytorch_checkpoint_to_pytorch.py
- convert_t5_original_tf_checkpoint_to_pytorch.py
- convert_transfo_xl_original_tf_checkpoint_to_pytorch.py
- convert_xlm_original_pytorch_checkpoint_to_pytorch.py
- convert_xlnet_original_tf_checkpoint_to_pytorch.py
- file.py
- file_utils.py
- filep.py
- hf_api.py
- modelcard.py
- modeling_albert.py
- modeling_auto.py
- modeling_bart.py
- modeling_beam_search.py
- modeling_bert.py
- modeling_camembert.py
- modeling_ctrl.py
- modeling_distilbert.py
- modeling_electra.py
- modeling_encoder_decoder.py
- modeling_flaubert.py
- modeling_gpt2.py
- modeling_mmbt.py
- modeling_openai.py
- modeling_roberta.py
- modeling_t5.py
- modeling_tf_albert.py
- modeling_tf_auto.py
- modeling_tf_bert.py
- modeling_tf_camembert.py
- modeling_tf_ctrl.py
- modeling_tf_distilbert.py
- modeling_tf_electra.py
- modeling_tf_flaubert.py
- modeling_tf_gpt2.py
- modeling_tf_openai.py
- modeling_tf_pytorch_utils.py
- modeling_tf_roberta.py
- modeling_tf_t5.py
- modeling_tf_transfo_xl.py
- modeling_tf_transfo_xl_utilities.py
- modeling_tf_utils.py
- modeling_tf_xlm.py
- modeling_tf_xlm_roberta.py
- modeling_tf_xlnet.py
- modeling_transfo_xl.py
- modeling_transfo_xl_utilities.py
- modeling_utils.py
- modeling_xlm.py
- modeling_xlm_roberta.py
- modeling_xlnet.py
- optimization.py
- optimization_tf.py
- pipelines.py
- tokenization_albert.py
- tokenization_auto.py
- tokenization_bart.py
- tokenization_bert.py
- tokenization_bert_japanese.py
- tokenization_camembert.py
- tokenization_ctrl.py
- tokenization_distilbert.py
- tokenization_electra.py
- tokenization_flaubert.py
- tokenization_gpt2.py
- tokenization_openai.py
- tokenization_roberta.py
- tokenization_t5.py
- tokenization_transfo_xl.py
- tokenization_utils.py
- tokenization_utils_base.py
- tokenization_xlm.py
- tokenization_xlm_roberta.py
- tokenization_xlnet.py
- try.py
- utils_encoder_decoder.py
Clustering.py
con_training_sts.py
README.md
requirements.txt
SemanticSearch.py
training_nli.py
training_sts.py

# Installation Guide

1. Get the code

git clone https://github.com/BM-K/KoSentenceBERT-SKT

Downloads the entire project code from GitHub to your computer.

cd KoSentenceBERT-SKT

Moves into the project folder you just downloaded.

2. Official Install Script

Easy Recommended

Prerequisites

Python 3 Python is required to use pip.

pip install .

Installs the package published on PyPI directly — no need to clone the source.

✅ After installing, open a new terminal and run the program's version command (e.g. --version) to confirm it worked.

Pulled directly from this repo's README.

3. Python

Easy

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install -r requirements.txt

Installs the Python libraries listed in requirements.txt (or similar).

pip install .

Installs the package published on PyPI directly — no need to clone the source.

✅ If it runs without errors and prints output in the terminal, it worked.

Pulled directly from this repo's README.