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NLP NLP

My links for models and libraries for the NLP downstrem tasks:

BERT from: https://github.com/google-research/bert

BERT pretrained model: https://github.com/google-research/bert#pre-trained-models

PyTorch Pretrained Bert: https://github.com/huggingface/transformers/tree/v0.4.0

RoBERTa : https://github.com/facebookresearch/fairseq/blob/main/examples/roberta/README.md

RoBERTa from huggingface: https://huggingface.co/docs/transformers/model_doc/roberta

KeyBERT from: https://github.com/MaartenGr/KeyBERT

Word2Vec from: https://code.google.com/archive/p/word2vec/

GloVe from: https://nlp.stanford.edu/projects/glove/

YAKE from: https://github.com/LIAAD/yake

spaCy from: https://github.com/explosion/spaCy

scispaCy from: https://github.com/allenai/scispacy

SBERT pretrained model or Sentence-transformers Pretrained Models from: https://www.sbert.net/docs/pretrained_models.html

Third party NLP models in the Elastic Stack: https://www.elastic.co/guide/en/machine-learning/master/ml-nlp-model-ref.html

HuggingFace - The AI community building the future: https://huggingface.co/

HuggingFace -Transfermers: https://huggingface.co/docs/transformers/index

HuggingFace -Transfermers from Github: https://github.com/huggingface/transformers

HuggingFace -Models: https://huggingface.co/models

BertViz - Visualize Attention in NLP Models: https://github.com/jessevig/bertviz

LSTM - Understanding LSTM Networks: http://colah.github.io/posts/2015-08-Understanding-LSTMs/

NLP models from Papers-with-code: https://paperswithcode.com/methods/area/natural-language-processing

Semantic Textual Similarity: https://paperswithcode.com/task/semantic-textual-similarity

Hedwig: This repo contains PyTorch deep learning models for document classification, implemented by the Data Systems Group at the University of Waterloo: https://github.com/castorini/hedwig

Keyword extraction method by combining the Rapid Automatic Keyword Extraction (RAKE) algorithm withthe NLTK toolkit gensim.summarization import keywords: https://github.com/csurfer/rake-nltk

Code to perform training, inference, and evaluation for 9 Topic Modeling packages https://github.com/d2klab/tomodapi

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