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dselivanov / text2vec

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cbaziotis / datastories-semeval2017-task4

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Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".

nlp twitter deep-learning sentiment-analysis neural-network word-embeddings keras embeddings lstm attention deeplearning glove computational-linguistics semeval attention-mechanism keras-models nlp-machine-learning twitter-messages semeval-sentiment
  • Updated Jun 8, 2018
  • Python

shayneobrien / coreference-resolution

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error when evaluating

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txAnnie
txAnnie commented Mar 28, 2019

Evaluating on validation corpus...
217it [12:27, 5.54s/it]Traceback (most recent call last):
File "./src/coref.py", line 690, in
trainer.train(150)
File "./src/coref.py", line 467, in train
results = self.evaluate(self.val_corpus)
File "./src/coref.py", line 566, in evaluate
predicted_docs = [self.predict(doc) for doc in tqdm(val_corpus)]
File "./src/coref.p

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guillaume-chevalier / GloVe-as-a-TensorFlow-Embedding-Layer

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Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.

neural-network tensorflow gpu word2vec word-embeddings gpu-acceleration gpu-tensorflow cosine-similarity glove glove-embeddings tensorflow-layers
  • Updated Oct 13, 2018
  • Jupyter Notebook

DiceTechJobs / VectorsInSearch

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Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the Activate 2018 search conference, and the 'Searching with Vectors' talk from Haystack 2019 (US). Builds upon my conceptual search and semantic search work from 2015

search-engine elasticsearch information-retrieval solr word2vec vector lsh locality-sensitive-hashing lucene kmeans glove quantization semantic-search bert invertedindex conceptual-search vector-quantization kmeans-quantization elmo inverted-indexes
  • Updated Feb 12, 2020
  • Python

luopeixiang / textclf

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TextClf ：基于Pytorch/Sklearn的文本分类框架，包括逻辑回归、SVM、TextCNN、TextRNN、TextRCNN、DRNN、DPCNN、Bert等多种模型，通过简单配置即可完成数据处理、模型训练、测试等过程。

sentiment-analysis label svm word2vec pytorch logistic-regression document-classification glove configurable bert sklearn-classify drnn textcnn textrnn cnn-text-classification dpcnn lstm-text-classification neuralclassifier
  • Updated Mar 8, 2020
  • Python

finalfusion / finalfusion-rust

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Add support for embedding pruning

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danieldk
danieldk commented Jul 31, 2019

Add support for pruning embeddings, where N embeddings are retained. Words for which embeddings are removed are mapped to their nearest neighbor.

This should provide more or less the same functionality as pruning in spaCy:

https://spacy.io/api/vocab#prune_vectors

I encourage some investigation here. Some ideas:

  1. The most basic version could simply retain the embeddings of the N most
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