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---
datasets:
- upb-nlp/same_topic_articles
language:
- ro
- en
base_model:
- FacebookAI/xlm-roberta-large
---
<div align="center">
<img src="images/logo.png" alt="Logo" width="240" height="240">
</div>
## How to Get Started with the Model
Use the code below to get started with the model.
```python
import torch
from transformers import AutoTokenizer, XLMRobertaForSequenceClassification
MODEL_PATH = "upb-nlp/xlm_roberta_large_article_same_topic_classification"
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = XLMRobertaForSequenceClassification.from_pretrained(MODEL_PATH, num_labels=2).to('cuda')
model.eval()
t1 = "Article title. Article body."
t2 = "Article title. Article body."
inputs = tokenizer(
t1,
t2,
return_tensors="pt",
truncation=True,
padding='max_length',
max_length=512
).to('cuda')
# Generate prediction
with torch.no_grad():
outputs = model(**inputs)
logits = outputs.logits
predicted_class = torch.argmax(logits, dim=1).item()
print(predicted_class)
``` |