Text Classification
Transformers
Safetensors
Arabic
bert
sentiment-analysis
arabic
text-embeddings-inference
Instructions to use TheMohanad1/marbert-arabic-sentiment-analyzer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheMohanad1/marbert-arabic-sentiment-analyzer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TheMohanad1/marbert-arabic-sentiment-analyzer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TheMohanad1/marbert-arabic-sentiment-analyzer") model = AutoModelForSequenceClassification.from_pretrained("TheMohanad1/marbert-arabic-sentiment-analyzer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 314 Bytes
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language: [ar]
pipeline_tag: text-classification
library_name: transformers
tags:
- sentiment-analysis
- arabic
base_model: UBC-NLP/MARBERTv2
license: other
---
# Arabic Sentiment Analysis (MARBERTv2)
نموذج لتحليل المشاعر بالعربية تم تدريبه على بيانات مخصّصة.
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