Text Classification
Transformers
Safetensors
Arabic
xlm-roberta
semantic-highlighting
arabic
sentence-relevance
rag
reranker
Eval Results (legacy)
text-embeddings-inference
Instructions to use HeshamHaroon/arabic-semantic-highlighter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HeshamHaroon/arabic-semantic-highlighter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HeshamHaroon/arabic-semantic-highlighter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HeshamHaroon/arabic-semantic-highlighter") model = AutoModelForSequenceClassification.from_pretrained("HeshamHaroon/arabic-semantic-highlighter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8319544814417cb6a4f7aee669726f5c56d20fbcc00661a62959290daee848e1
- Size of remote file:
- 1.11 GB
- SHA256:
- 0cfd398375f844acca5a5d5470a7358fbfc0bb3c711a0f05d11b810cb31757e5
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