README.md

JAIS-6p7b-Chat: State-of-the-art large language model useful on a variety of language understanding and generation tasks

JAIS 6.7B is a bilingual large language model (LLM) for both Arabic and English developed by Inception, a G42 company in partnership with MBZUAI and Cerebras. This is a 6.7 billion parameter LLM, trained on a dataset containing 141 billion Arabic tokens and 339 billion English/code tokens. The model is based on transformer-based decoder-only (GPT-3) architecture and uses SwiGLU non-linearity. It implements ALiBi position embeddings, enabling the model to extrapolate to long sequence lengths, providing improved context handling and model precision. The JAIS family of models is a comprehensive series of bilingual English-Arabic LLMs. These models are optimized to excel in Arabic while having strong English capabilities.

This is based on the implementation of JAIS-6p7b-Chat found here. This repository contains scripts for optimized on-device export suitable to run on Qualcomm® devices. More details on model performance accross various devices, can be found here.

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Deploying JAIS-6p7b-Chat on-device

Please follow the LLM on-device deployment tutorial.

References

• Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models
• Source Model Implementation

Community

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• For questions or feedback please reach out to us.

Usage and Limitations

This model may not be used for or in connection with any of the following applications:

• Accessing essential private and public services and benefits;
• Administration of justice and democratic processes;
• Assessing or recognizing the emotional state of a person;
• Biometric and biometrics-based systems, including categorization of persons based on sensitive characteristics;
• Education and vocational training;
• Employment and workers management;
• Exploitation of the vulnerabilities of persons resulting in harmful behavior;
• General purpose social scoring;
• Law enforcement;
• Management and operation of critical infrastructure;
• Migration, asylum and border control management;
• Predictive policing;
• Real-time remote biometric identification in public spaces;
• Recommender systems of social media platforms;
• Scraping of facial images (from the internet or otherwise); and/or
• Subliminal manipulation