Download the word2vec model from https://code.google.com/archive/p/word2vec/ and download the file: GoogleNews-vectors-negative300.bin.gz Set training=False if you want to load trained weights Files:
- semtrain.p- training data (SemEval 2014)
- semtest.p- testing date (SemEval 2014)
- stsallrmf.p- all STS data.
Scripts: (in examples folder)
- example1.py : Load trained model to predict sentence similarity on a scale of 1.0-5.0
- example2.py : Load trained model and check Pearson, Spearman and MSE.
- example3.py : Train the model (takes a long time to compile gradients)
- examples.ipynb : explanation of the MaLSTM code (iPython notebook)
Mueller, J and Thyagarajan, A. Siamese Recurrent Architectures for Learning Sentence Similarity. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016). http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12195