feat: add README

README.md

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 license: mit
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+
+# Language Detection
+
+A lightweight language detection tool that uses character-level n-gram features and logistic regression to identify the language of a given text.
+
+Supported languages out of the box: English, French, German, Turkish.
+
+Model repository: https://huggingface.co/Isa0/language-detection/
+
+## Installation
+
+Requires Python 3.11 or higher. Install dependencies with [uv](https://github.com/astral-sh/uv):
+
+```bash
+uv sync
+```
+
+## Usage
+
+### Train
+
+Train the model on the datasets in the `datasets/` directory:
+
+```bash
+uv run main.py --train
+```
+
+You can point it to a different directory with `--dir`:
+
+```bash
+uv run main.py --train --dir path/to/datasets
+```
+
+Each `.txt` file in the directory should contain one sentence per line. The filename (without extension) is used as the language label.
+
+### Detect
+
+Detect the language of a text string:
+
+```bash
+uv run main.py --detect "Bonjour, comment allez-vous?"
+```
+
+Output includes the predicted language and a confidence score.
+
+## Adding Languages
+
+Add a new `.txt` file to the `datasets/` directory named after the language (e.g. `spanish.txt`), with one sentence per line, then retrain.
+
+## How It Works
+
+Text is converted into character-level n-gram counts (1 to 3 characters), which capture language-specific patterns like accents, letter combinations, and suffixes. A logistic regression classifier is trained on these features and saved to disk for reuse.