running glove on windows
来源： https://stackoverflow.com/questions/51463453/running-glove-on-windows
glove
Improving on the basic, existing GloVe model
来源： https://stackoverflow.com/questions/43618145/improving-on-the-basic-existing-glove-model
Improving on the basic, existing GloVe model
来源： https://stackoverflow.com/questions/43618145/improving-on-the-basic-existing-glove-model
Using pretrained glove word embedding with scikit-learn
问题 I have used keras to use pre-trained word embeddings but I am not quite sure how to do it on scikit-learn model. I need to do this in sklearn as well because I am using vecstack to ensemble both keras sequential model and sklearn model. This is what I have done for keras model: glove_dir = '/home/Documents/Glove' embeddings_index = {} f = open(os.path.join(glove_dir, 'glove.6B.200d.txt'), 'r', encoding='utf-8') for line in f: values = line.split() word = values[0] coefs = np.asarray(values[1:
averaging a sentence’s word vectors in Keras- Pre-trained Word Embedding
问题 I am new to Keras. My goal is to create a Neural Network Multi-Classification for Sentiment Analysis for tweets. I used Sequential in Keras to build my model. I want to use pre-trained word embeddings in the first layer of my model, specifically gloVe . Here is my model currently: model = Sequential() model.add(Embedding(vocab_size, 300, weights=[embedding_matrix], input_length=max_length, trainable=False)) model.add(LSTM(100, stateful=False)) model.add(Dense(8, input_dim=4, activation='relu'
Glove6b50d parsing: could not convert string to float: '-'
问题 I am trying to parse the Glove6b50d data from Kaggle in via Google Colab, then run it through the word2vec process (apologies for the huge URL - it's the fastest link I've found). However, I'm hitting a bug where '-' tokens are not parsed correctly, resulting in the above error. I have attempted to handle this in a few ways. I've also looked into the load_word2vec_format method itself and tried to ignore errors, however it doesn't seem to make a difference. I've tried a map method on line two
Glove6b50d parsing: could not convert string to float: '-'
问题 I am trying to parse the Glove6b50d data from Kaggle in via Google Colab, then run it through the word2vec process (apologies for the huge URL - it's the fastest link I've found). However, I'm hitting a bug where '-' tokens are not parsed correctly, resulting in the above error. I have attempted to handle this in a few ways. I've also looked into the load_word2vec_format method itself and tried to ignore errors, however it doesn't seem to make a difference. I've tried a map method on line two
How to use a pre-trained embedding matrix in tensorflow 2.0 RNN as initial weights in an embedding layer?
问题 I'd like to use a pretrained GloVe embedding as the initial weights for an embedding layer in an RNN encoder/decoder. The code is in Tensorflow 2.0. Simply adding the embedding matrix as a weights = [embedding_matrix] parameter to the tf.keras.layers.Embedding layer won't do it because the encoder is an object and I'm not sure now to effectively pass the embedding_matrix to this object at training time. My code closely follows the neural machine translation example in the Tensorflow 2.0
How to Train GloVe algorithm on my own corpus
问题 I tried to follow this. But some how I wasted a lot of time ending up with nothing useful. I just want to train a GloVe model on my own corpus (~900Mb corpus.txt file). I downloaded the files provided in the link above and compiled it using cygwin (after editing the demo.sh file and changed it to VOCAB_FILE=corpus.txt . should I leave CORPUS=text8 unchanged?) the output was: cooccurrence.bin cooccurrence.shuf.bin text8 corpus.txt vectors.txt How can I used those files to load it as a GloVe
How to Train GloVe algorithm on my own corpus
I tried to follow this. But some how I wasted a lot of time ending up with nothing useful. I just want to train a GloVe model on my own corpus (~900Mb corpus.txt file). I downloaded the files provided in the link above and compiled it using cygwin (after editing the demo.sh file and changed it to VOCAB_FILE=corpus.txt . should I leave CORPUS=text8 unchanged?) the output was: cooccurrence.bin cooccurrence.shuf.bin text8 corpus.txt vectors.txt How can I used those files to load it as a GloVe model on python? You can do it using GloVe library: Install it: pip install glove_python Then: from glove