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AI-team-UoA/
GreekDeBERTaV3-base

Name: GreekDeBERTaV3-base
Availability: InStock

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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")