Instructions to use qandos0/SentimentArEng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qandos0/SentimentArEng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="qandos0/SentimentArEng")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("qandos0/SentimentArEng") model = AutoModelForSequenceClassification.from_pretrained("qandos0/SentimentArEng") - Notebooks
- Google Colab
- Kaggle
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This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on the None dataset.
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It achieves the following results on the evaluation set:
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# SentimentArEng
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This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on the None dataset.
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It achieves the following results on the evaluation set:
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