caver 0.0.6

Multi-label Text Classification Toolkit

# Caver: a toolkit for multilabel text classification.

[中文版](./README_zh.md)

---

Rising a torch in the cave to see the words on the wall. This is the `Caver`.

[Documents](https://guokr.github.io/Caver)

## Requirements

* PyTorch
* tqdm
* torchtext
* scipy
* numpy
* Python3

## How to train on your onw dataset

```python

python3 train.py --input_data_dir {path to your origin dataset} --output_data_dir {path to store the preprocessed dataset} --train_filename train.tsv --valid_filename valid.tsv --checkpoint_dir {path to save the checkpoints} --model {fastText/CNN/LSTM} --batch_size {16, you can modify this for you own} --epoch {10}

```

## Did you guys have some pre-trained models

Yes

## How to setup the models for inference

Basicly just setup the model and target labels, you can check examples in server.py and ensemble.py