Text Classification
Transformers
TensorBoard
Safetensors
Arabic
bert
Generated from Trainer
text-embeddings-inference
Instructions to use PRAli22/AraBert-Arabic-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PRAli22/AraBert-Arabic-Sentiment-Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PRAli22/AraBert-Arabic-Sentiment-Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PRAli22/AraBert-Arabic-Sentiment-Analysis") model = AutoModelForSequenceClassification.from_pretrained("PRAli22/AraBert-Arabic-Sentiment-Analysis") - Notebooks
- Google Colab
- Kaggle
Dataset
#1
by nzm97 - opened
On what dataset the model was trained on ?
it will be very helpful if you share this information.
it was trained on Arabic tweets and a corpus of Arabic tweets in the Saudi dialect annotated with four labels: positive, negative, neutral, mixed the dataset was published on particular licenses so i can not publish it