---
license: mit
language:
- el
pipeline_tag: text-classification
---
# 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:

```python
from transformers import AutoTokenizer, AutoModelForTokenClassification

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