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torchMoji examples
Initialization
create_twitter_vocab.py Create a new vocabulary from a tsv file.
tokenize_dataset.py Tokenize a given dataset using the prebuilt vocabulary.
vocab_extension.py Extend the given vocabulary using dataset-specific words.
dataset_split.py Split a given dataset into training, validation and testing.
Use pretrained model/architecture
score_texts_emojis.py Use torchMoji to score texts for emoji distribution.
text_emojize.py
Use torchMoji to output emoji visualization from a single text input (mapped from emoji_overview.png
)
python examples/text_emojize.py --text "I love mom's cooking\!"
# => I love mom's cooking! π π π π β€
encode_texts.py Use torchMoji to encode the text into 2304-dimensional feature vectors for further modeling/analysis.
Transfer learning
finetune_youtube_last.py Finetune the model on the SS-Youtube dataset using the 'last' method.
finetune_insults_chain-thaw.py Finetune the model on the Kaggle insults dataset (from blog post) using the 'chain-thaw' method.
finetune_semeval_class-avg_f1.py Finetune the model on the SemeEval emotion dataset using the 'full' method and evaluate using the class average F1 metric.