| Model Type | | large language model, bilingual, auto-regressive, transformer-based, decoder-only | 
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| Use Cases | 
| Areas: |  |  | Applications: | | Chat applications, Sentiment analysis, Document summarization | 
 |  | Primary Use Cases: | | Arabic Natural Language Processing, Developing chat assistants, Mechanistic interpretability analyses | 
 |  | Limitations: | | Limited to responses in Arabic and English, Potential for generating biased or incorrect information | 
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| Supported Languages | | primary_language (Arabic), other_languages (English) | 
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| Training Details | 
| Data Sources: | | Web pages, Wikipedia articles, News articles, Social network content, Code data, Books, Scientific papers, Synthetic translation | 
 |  | Data Volume: |  |  | Methodology: | | Pre-trained from scratch or adaptively from Llama-2 | 
 |  | Context Length: |  |  | Hardware Used: | | Condor Galaxy (CG) supercomputer platform, Cerebras CS-2 Wafer-Scale Engines | 
 |  | Model Architecture: | | Transformer-based, decoder-only architecture using SwiGLU and ALiBi for Jais models and RoPE with Grouped Query Attention for adapted models | 
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| Responsible Ai Considerations | 
| Mitigation Strategies: | | Multiple techniques to reduce bias, but some bias and errors are likely. | 
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| Input Output | 
| Input Format: |  |  | Output Format: |  |  |