GreekDeBERTaV3-base

GreekDeBERTaV3-base

GreekDeBERTaV3-base is a language model pre-trained specifically for Greek NLP tasks. It is based on the DeBERTaV3 architecture, incorporating improvements from the replaced token detection (RTD) task during pre-training.

Model Overview

• Model Architecture: DeBERTaV3-base
• Language: Greek
• Pre-training Tasks: Replaced Token Detection (RTD)
• Tokenizer: SentencePiece Model (spm.model)

This model was trained on a diverse corpus of Greek texts and is suitable for tasks like Part-of-Speech tagging, Named Entity Recognition, and Natural Language Inference.

Files

• config.json: Configuration file for the model.
• pytorch_model.bin: The PyTorch weights of the model.
• spm.model: The SentencePiece tokenizer model.
• vocab.txt: A human-readable vocabulary file that contains the list of tokens used by the model.
• tokenizer_config.json: Tokenizer configuration file.

How to Use

You can use this model with the Hugging Face transformers library:

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("AI-team-UoA/GreekDeBERTaV3-base")
model = AutoModelForTokenClassification.from_pretrained("AI-team-UoA/GreekDeBERTaV3-base")