Model Type | bilingual, large language model, text generation |
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Use Cases |
Areas: | |
Applications: | Natural language understanding and generation, Mechanistic interpretability analyses, Chat assistants, Sentiment analysis, Document summarization |
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Primary Use Cases: | Arabic and English language tasks |
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Limitations: | Handling or generating personal, confidential, or sensitive information, High-stakes decisions without human oversight |
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Considerations: | Model should not be used beyond its designed language proficiency or for making critical decisions without human involvement. |
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Additional Notes | The model unlocks numerous use cases in Arabic NLP, with strategies extensible to other low and medium resource languages. |
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Supported Languages | languages_supported (Arabic (MSA), English), proficiency (Optimized for Arabic, strong in English) |
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Training Details |
Data Sources: | Web, Code, Books, Scientific, Synthetic, ArXiv papers |
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Data Volume: | |
Methodology: | Instruction fine-tuned for dialog |
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Context Length: | |
Hardware Used: | Cerebras CS-2 Wafer-Scale Engines |
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Model Architecture: | Transformer-based, decoder-only architecture, Jais models are trained from scratch, while Jais adapted models are built on Llama-2. |
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Safety Evaluation |
Methodologies: | Bias and misinformation assessments |
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Risk Categories: | |
Ethical Considerations: | Prohibits use for harmful, misleading, or inappropriate content. |
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Responsible Ai Considerations |
Fairness: | Efforts made to minimize biases, but biases may still be present. |
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Transparency: | The training and tuning processes are documented. |
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Accountability: | Users must ensure the model is used ethically and legally. |
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Mitigation Strategies: | Incorporated fine-tuning with diverse Arabic-English prompt-response pairs. |
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Input Output |
Input Format: | Text prompts in either Arabic or English |
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Accepted Modalities: | |
Output Format: | |
Performance Tips: | Model is optimized for bilingual tasks; ensure prompts are framed within supported languages. |
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Release Notes |
Version: | |
Date: | |
Notes: | Introduction of 20 models across various sizes, featuring improved context handling and precision. |
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