Metadata-Version: 2.1
Name: lancetnic
Version: 1.2.1
Summary: A tool for working with text data
Home-page: https://github.com/Lancet52/lancetnic
Author: Lancet52
Author-email: lancetFPV@yandex.ru
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE

# LANCETNIC 1.2.1

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The LANCETNIC library is a tool for working with text data: learning, analysis, and inference.

Tasks to be solved:
- Binary classification (spam/not spam; patient is sick/not sick; loan approved/refusal, etc.)


## 🚀 Installing:
Install with CUDA

To work with the GPU, it is recommended to install PyTorch with CUDA support (OPTIONAL):

```bash
pip install torch==2.5.1+cu124 torchaudio==2.5.1+cu124 torchvision==0.20.1+cu124 --index-url https://download.pytorch.org/whl/cu124
```

Then install lancetnic:

```bash
pip install lancetnic
```

## 👥 Autors

- [Lancet52](https://github.com/Lancet52)

## 📄 Documentation

### [Документация на русском](https://github.com/Lancet52/lancetnic/blob/main/lancetnic/docs/RU.md)
### [Documentation in English](https://github.com/Lancet52/lancetnic/blob/main/lancetnic/docs/EN.md)

## Quick start
Training:
```Python
from lancetnic.models import LancetBC
from lancetnic import Binary

model = Binary()
model.train(model_name=LancetBC, # A model for binary classification
            train_path="train.csv", # The path to the training dataset
            val_path="val.csv", # Path to the validation dataset
            num_epochs=50 # Number of training epochs
            )
            
```
Inferece:
```Python
from lancetnic import Predictor
pred=Predictor()
prediction=pred.predict(model_path="best_model.pt",
             text="Your text"
             )

print(prediction)
```
