Text Classification
Transformers
Safetensors
Arabic
bert
arabic
arabert
social-media-analysis
threat-detection
streamlit
text-embeddings-inference
Instructions to use SoftALL/OBSIDIAN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SoftALL/OBSIDIAN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SoftALL/OBSIDIAN")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SoftALL/OBSIDIAN") model = AutoModelForSequenceClassification.from_pretrained("SoftALL/OBSIDIAN") - Notebooks
- Google Colab
- Kaggle
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- **University:** King Fahd University of Petroleum & Minerals (KFUPM)
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- **College:** College of Computing and Mathematics
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- **Department:** Department of Computer Engineering
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- **Degree Program:** Master’s Degree in Computer Engineering
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- **Academic Year:** 2024–2026
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- **University:** King Fahd University of Petroleum & Minerals (KFUPM)
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- **College:** College of Computing and Mathematics
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- **Department:** Department of Computer Engineering / Computer Networks Program
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- **Degree Program:** Master’s Degree in Computer Engineering
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- **Academic Year:** 2024–2026
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