pytorch-wordemb

Load pretrained word embeddings (word2vec, glove format) into torch.FloatTensor for PyTorch

Install

PyTorch required. Please follow the official site installation guide.

pip install cffi
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")

vocab, vec = torchwordemb.load_word2vec_bin("./resource/word2vec.test.bin")

print(vec.size())
print(vec[vocab["user"]])

# print(vec[ w2v.vocab["apple"] ] )

torchwordemb.load_word2vec_text(path)

read word2vec text-format model from path.

import torchwordemb

# load FT format (.vec)
vocab, vec = torchwordemb.load_word2vec_text("/path/to/file.vec")

print(vec.size())
print(vec[vocab["老鼠會"]])

torchwordemb.load_glove_text(path)