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🧠 Urdu Sentiment Analysis Model
This model performs sentiment analysis on Urdu text using a fine‑tuned XLM-RoBERTa transformer model.
It classifies input text into:
✅ Positive
❌ Negative
⚖️ Neutral
📊 Model Details
- Architecture: XLM-RoBERTa
- Framework: PyTorch
- Task: Text Classification (Sentiment Analysis)
- Language: Urdu
🚀 Usage Example
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
model_name = "abd12-tahir/urdu-sentiment-model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)
text = "میں آج بہت خوش ہوں"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
pred = torch.argmax(outputs.logits, dim=1)
print(pred)
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