semvec/pypi-packages huggingface dataset:
mugees 0.0.0.1
A python library for detecting depressive comments
Requires Python: >=3.6

<div align="center">

#   Mugees
##  Depression Comment Classification with Transformers

</div>

Dependencies:
- For inference:
  - Transformers
  - Pytorch lightning
- For training will also need:
  - Kaggle API (to download data)


# install mugees

pip install mugees

```
python

from mugees import Depression

# each model takes in either a string or a list of strings

results = Depression('original').predict('example text')

results = Depression('unbiased').predict(['example text 1','example text 2'])

results = Depression('multilingual').predict(['example text','exemple de texte','texto de ejemplo','testo di esempio','texto de exemplo','örnek metin','пример текста'])

# to specify the device the model will be allocated on (defaults to cpu), accepts any torch.device input

model = Depression('original', device='cuda')

# optional to display results nicely (will need to pip install pandas)

import pandas as pd

print(pd.DataFrame(results, index=input_text).round(5))

```

Importing mugees in python:

```
python

from mugees import Depression

results = Depression('original').predict('some text')

results = Depression('unbiased').predict(['example text 1','example text 2'])

results = Depression('multilingual').predict(['example text','exemple de texte','texto de ejemplo','testo di esempio','texto de exemplo','örnek metin','пример текста'])

# to display results nicely

import pandas as pd

print(pd.DataFrame(results,index=input_text).round(5))
```