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code-switching-codesaviours-si26-sumair
Sumair-Parveiz/code-switching-codesaviours-si26-sumair
code-switching-codesaviours-si26-sumair is a token classification model from Sumair-Parveiz. Use it when you need labels on individual words, such as names. The card lists the license as apache-2.0.
This model is a fine-tuned version of XLM-RoBERTa (base) trained for token-level language identification in Roman Urdu and English text.
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At a glance
- Task
- Token Classification
- License
- apache-2.0
- Model type
- xlm-roberta
- Access
- Public
- Created
- Aug 13, 2026
- Updated
- Aug 20, 2026
- SHA
- 9f2df369
Base models
Model card
From the Hugging Face model README
Model for Code-Switched Roman Urdu & English
This model is a fine-tuned version of XLM-RoBERTa (base) trained for token-level language identification in Roman Urdu and English text.
Intended Use & Task
- Task: Token Classification (Language Identification)
- Labels:
0 / URD: Roman Urdu token1 / ENG: English token2 / MIX: Code-switched / Hybrid / Localized token
Performance & Evaluation Metrics
Evaluated on test set tokens:
| Class | Precision | Recall | F1-Score |
|---|---|---|---|
| URD | 1.00 | 0.98 | 0.99 |
| ENG | 0.96 | 1.00 | 0.98 |
| MIX | 0.89 | 0.80 | 0.84 |
| Accuracy | — | — | 0.98 |
How to Use
from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
model_id = "Sumair-Parveiz/code-switching-codesaviours-si26-sumair"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForTokenClassification.from_pretrained(model_id)
nlp = pipeline("token-classification", model=model, tokenizer=tokenizer)
example = "Main abhi sochoing mode mein hoon"
print(nlp(example))
- Task
- Token Classification
- Type
- xlm-roberta
- License
- apache-2.0
- Languages
- ur, en
- Created
- Aug 13, 2026
- Updated
- Aug 20, 2026