# 🇳🇬 **Zuba Language Classifier**

**Zuba Language Classifier** is a lightweight Python package for classifying text into four major Nigerian languages:

* **Hausa**
* **Yoruba**
* **Igbo**
* **Broken English (Pidgin)**

The model is built using a fine-tuned **GPT-2 architecture** and loads automatically from the **HuggingFace Hub**, so you do **not** need to download or bundle any model files manually.

The package supports both single-sentence and batch predictions.

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##  Features

* Predicts **four Nigerian languages**
*  Works with **single strings or lists**
* Auto-downloads model from **HuggingFace Hub**
* Fast inference and minimal dependencies

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##  Installation

Install the package from **PyPI**:

```bash
pip install zuba
```

Install **PyTorch** if you do not already have it:

```bash
pip install torch
```

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##  Model Setup

The classifier automatically downloads the trained GPT-2 model from the **HuggingFace Hub** the first time you use it.

No manual setup is required.

You may also use a custom model if your architecture differs.

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## 🚀 Quick Start

```python
from Zuba.Prediction import Classify

Classifier = Classify()

classifier=Classify()
result=classifier.predict([
    
        "Ina jin dadin wannan rana.",
        "Mo fẹ jẹ iyan.",
        "A na m aga ahịa echi."
    
])
print(result)
```

**Output:**

```text
["hausa", "yoruba", "igbo"]
```

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## ⚙️ How It Works

1. Your model class is loaded by the `Classify` constructor.
2. The package downloads the trained weights from HuggingFace automatically.
3. Text is tokenized with **GPT-2 tokenizer (tiktoken)**.
4. Input is encoded, padded, and truncated to the required sequence length.
5. The model performs inference and outputs one of the four language labels.

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### **classifier.py**

Handles tokenization, preprocessing, batching, and predictions.

### **model_loader.py**

Downloads and loads the trained model weights from HuggingFace.

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## 🔧 Configuration

**Tokenization Length**

The default maximum token length is:

```text
277
```


## 🔗 Important Constants

```python
REPO_ID = "your-username/your-repo-name"
PACKAGE_LINK = "PYPI_link"
```

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## 📜 License

This project is licensed under the **MIT License**.

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