---

language:

• km license: apache-2.0 tags:
• xlm-roberta
• khmer
• tokenizer
• masked-lm datasets:
• custom-khmer-dataset widget:
• text: "ខ្ញុំចង់ភាសាខ្មែរ"

---

XLM-RoBERTa Khmer Custom Tokenizer

This is a custom tokenizer trained for Khmer language based on XLM-RoBERTa architecture.

Model Details

• Model Type: XLM-RoBERTa Tokenizer
• Language: Khmer (km)
• Training Data: Custom Khmer dataset with ~84M examples
• Tokenizer Type: SentencePiece-based

Usage

from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("metythorn/xlm-roberta-tokenizer-100k")

# Example usage
text = "ខ្ញុំចង់រៀនភាសាខ្មែរ"
tokens = tokenizer.tokenize(text)
print(tokens)

Training Details

• Base model: XLM-RoBERTa
• Training examples: 84Million
• Epochs: 3
• Batch size: 8
• Parameters: 278,295,186

Intended Use

This tokenizer is designed for:

• Khmer text processing
• Masked language modeling
• Fine-tuning on Khmer NLP tasks
• Research in Khmer language understanding

Limitations

• Primarily trained on Khmer text
• May not handle code-switching effectively
• Performance on formal vs informal Khmer may vary