Workaround for word embeddings that do not "see" antonyms
You could probably use the technique to combine vectors with antonyms with some kind of weights. Below thread suggests adding POS tagger with word2vec vectors, instead of POS you can concatenate antonyms:

https://stats.stackexchange.com/questions/238016/deep-learning-word-embedding-with-parts-of-speech

https://stackoverflow.com/questions/51537441/how-to-combine-both-word-embeddings-and-pos-embedding-together-to-build-the-clas

You can identify Antonyms using below:

https://www.geeksforgeeks.org/get-synonymsantonyms-nltk-wordnet-python/