# RoBERTa Style Classifier

This is a fine-tuned [`roberta-base`](https://huggingface.co/roberta-base) model for **writing style classification**.

## 🔍 Task
Given an input sentence, the model predicts the most appropriate **writing style** such as:
- Empathetic
- Formal
- Casual
- Persuasive
- Technical
- ... and more

## 🧠 Model Details
- Base model: `roberta-base`
- Max length: 256 tokens
- Trained using PyTorch and Hugging Face Transformers
- Dataset: Custom curated and balanced dataset with 10+ writing styles

## 📊 Usage

```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model = AutoModelForSequenceClassification.from_pretrained("Akshay-Sai/roberta-style-classifier")
tokenizer = AutoTokenizer.from_pretrained("Akshay-Sai/roberta-style-classifier")

def predict_style(text):
    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=256)
    with torch.no_grad():
        outputs = model(**inputs)
        pred = torch.argmax(outputs.logits, dim=1)
    return model.config.id2label[pred.item()]

# Example
text = "I understand how tough this must be for you. Stay strong."
print("Predicted Style:", predict_style(text))