semvec/pypi-packages huggingface dataset:
entropix 2.0.1
Sampling SVD singular vectors for Distributional Semantics Models
License: MIT
Keywords: entropy,distributional semantics

# entropix
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[license-url]:LICENSE.txt

Generate count-based Distributional Semantic Models by sampling SVD singular vectors instead of using top components.

## Install
```shell
pip install entropix
```

or, after a git clone:
```shell
python3 setup.py install
```

## Use

### Sequential mode
```shell
entropix sample \
--model /abs/path/to/dense/numpy/model.npy \
--vocab /abs/path/to/corresponding/model.vocab \
--dataset dataset_to_optimize_on \  # men, simlex or simverb
--shuffle \
--mode seq \
--kfold-size .2 \  # size of kfold, between 0 and .5
--metric pearson \  # spr(spearman), pearson, rmse or both (spr+rmse)
--num-threads 5
```

### Limit mode
```shell
entropix sample \
--model /abs/path/to/dense/numpy/model.npy \
--vocab /abs/path/to/corresponding/model.vocab \
--dataset dataset_to_optimize_on \  # men, simlex or simverb
--mode limit \
--metric pearson \
--limit 10  # number of dimensions to sample
```