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41 lines
1.2 KiB
Markdown
41 lines
1.2 KiB
Markdown
# Castor
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PyTorch deep learning models.
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1. [SM model](./sm_cnn/): Similarity between question and candidate answers.
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## Setting up PyTorch
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You need Python 3.6 to use the models in this repository.
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As per [pytorch.org](pytorch.org),
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> "[Anaconda](https://www.continuum.io/downloads) is our recommended package manager"
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```conda install pytorch torchvision -c soumith```
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Other pytorch installation modalities (e.g. via ```pip```) can be seen at [pytorch.org](pytorch.org).
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We also recommend [gensim](https://radimrehurek.com/gensim/). We use some gensim modules to cache word embeddings.
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```conda install gensim```
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PyTorch has good support for GPU computations.
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CUDA installation guide for linux can be found [here](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/)
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**NOTE**: Install CUDA libraries **before** installing conda and pytorch.
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## data for models
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Sourcing and pre-processing of input data for each model is described in respective ```model/README.md```'s
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## Baselines
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1. [IDF Baseline](./idf_baseline/): IDF overlap between question and candidate answers.
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## Tutorials
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SM Model tutorial: [sm_cnn/tutorial.ipynb](sm_cnn/tutorial.ipynb) - notebook that walks through SM CNN model, good for beginnners.
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