Text Classification
Transformers
PyTorch
Arabic
bert
sentiment analysis
classification
arabic dialect
tunisian dialect
Instructions to use AhmedBou/TuniBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AhmedBou/TuniBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AhmedBou/TuniBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AhmedBou/TuniBert") model = AutoModelForSequenceClassification.from_pretrained("AhmedBou/TuniBert") - Notebooks
- Google Colab
- Kaggle
This is a fineTued Bert model on Tunisian dialect text (Used dataset: AhmedBou/Tunisian-Dialect-Corpus), ready for sentiment analysis and classification tasks.
LABEL_1: Positive
LABEL_2: Negative
LABEL_0: Neutral
This work is an integral component of my Master's degree thesis and represents the culmination of extensive research and labor. If you wish to utilize the Tunisian-Dialect-Corpus or the TuniBert model, kindly refer to the directory provided. [huggingface.co/AhmedBou][github.com/BoulahiaAhmed]
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