docs: Add text_tokenize.py example

examples/README.md

@@ -1,31 +1,39 @@
 # torchMoji examples
 
-## Initialization  
-[create_twitter_vocab.py](create_twitter_vocab.py)  
-Create a new vocabulary from a tsv file.  
-  
-[tokenize_dataset.py](tokenize_dataset.py)  
-Tokenize a given dataset using the prebuilt vocabulary.  
-  
-[vocab_extension.py](vocab_extension.py)  
-Extend the given vocabulary using dataset-specific words.  
-  
-[dataset_split.py](dataset_split.py)  
+## Initialization
+[create_twitter_vocab.py](create_twitter_vocab.py)
+Create a new vocabulary from a tsv file.
+
+[tokenize_dataset.py](tokenize_dataset.py)
+Tokenize a given dataset using the prebuilt vocabulary.
+
+[vocab_extension.py](vocab_extension.py)
+Extend the given vocabulary using dataset-specific words.
+
+[dataset_split.py](dataset_split.py)
 Split a given dataset into training, validation and testing.
-  
-## Use pretrained model/architecture 
-[score_texts_emojis.py](score_texts_emojis.py)  
-Use torchMoji to score texts for emoji distribution.  
 
-[encode_texts.py](encode_texts.py)  
+## Use pretrained model/architecture
+[score_texts_emojis.py](score_texts_emojis.py)
+Use torchMoji to score texts for emoji distribution.
+
+[text_emojize.py](text_emojize.py)
+Use torchMoji to output emoji visualization from a single text input (mapped from `emoji_overview.png`)
+
+```sh
+python examples/text_emojize.py --text "I love mom's cooking\!"
+# => I love mom's cooking! 😋 😍 💓 💛 ❤
+```
+
+[encode_texts.py](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_youtube_last.py)  
-Finetune the model on the SS-Youtube dataset using the 'last' method.  
-    
-[finetune_insults_chain-thaw.py](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_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.  
+[finetune_youtube_last.py](finetune_youtube_last.py)
+Finetune the model on the SS-Youtube dataset using the 'last' method.
+
+[finetune_insults_chain-thaw.py](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_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.