Load pretrained word embeddings (word2vec, glove format) into torch.FloatTensor for PyTorch
Project description
Load pretrained word embeddings (word2vec, glove format) into torch.FloatTensor for PyTorch
Install
PyTorch required.
pip install torchwordemb
Usage
import torchwordemb
torchwordemb.load_word2vec_bin(path)
read word2vec binary-format model from path.
returns (vocab, vec)
vocab is a dict mapping a word to its index.
vec is a torch.FloatTensor of size V x D, where V is the vocabulary size and D is the dimension of word2vec.
vocab, vec = torchwordemb.load_word2vec_bin("/path/to/word2vec/model.bin")
print(vec.size())
print(vec[ w2v.vocab["apple"] ] )
torchwordemb.load_word2vec_text(path)
read word2vec text-format model from path.
torchwordemb.load_glove_text(path)
read GloVe text-format model from path.
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