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:
- acd9b734b312d53d7c8cb1f006fbc40dd58fbcd4899b39457b2fca8d1b0ebe0a
- Size of remote file:
- 5.78 kB
- SHA256:
- be0ad0c4baf7bbfafb4f0e5edee081009ea9f8611c7d422822c0245787f41b62
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