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
- Xet hash:
- ff53bd2de965bef769c9f7ecd92146b5ea7bf60f04071f84dcd0e689d4358e49
- Size of remote file:
- 17.1 MB
- SHA256:
- 7edf6451773135b9bead462aa434bf6ffbb7ac59ccbfd1a5597a9f78f6dddfd2
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