Development of chat assistants, Sentiment analysis, Summarization of bilingual documents
Primary Use Cases:
Arabic and English NLP tasks, Cultural alignment analysis, Mechanistic interpretability
Additional Notes
Jais models are designed for Arabic and English tasks, not other languages.
Supported Languages
Arabic (high proficiency), English (strong capabilities)
Training Details
Data Sources:
Public web pages, Wikipedia, News articles, Social network content, Code in various languages, Books in Arabic and English, ArXiv papers, Synthetic translations of high-quality English resources
Data Volume:
Up to 1.6 trillion tokens
Methodology:
Two-stage training with frozen and unfrozen layers for adapted pre-training; progressive context length expansion
Context Length:
16384
Hardware Used:
Condor Galaxy supercomputer, 64 Cerebras CS-2 WSE-2 units
Model Architecture:
Transformer-based, decoder-only architecture with SwiGLU activation and ALiBi/ROPE position encoding
Note: green Score (e.g. "73.2") means that the model is better than inceptionai/jais-family-590m-chat.
Rank the Jais Family 590M Chat Capabilities
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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
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