Instructions to use Yah216/Sentiment_Analysis_CAMelBERT_msa_sixteenth_HARD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yah216/Sentiment_Analysis_CAMelBERT_msa_sixteenth_HARD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yah216/Sentiment_Analysis_CAMelBERT_msa_sixteenth_HARD")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yah216/Sentiment_Analysis_CAMelBERT_msa_sixteenth_HARD") model = AutoModelForSequenceClassification.from_pretrained("Yah216/Sentiment_Analysis_CAMelBERT_msa_sixteenth_HARD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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# Model description
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This model is an Arabic language sentiment analysis pretrained model.
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language: ar
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widget:
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- text: "أنا بخير"
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---
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# Model description
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This model is an Arabic language sentiment analysis pretrained model.
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