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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 across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Deploying JAIS-6p7b-Chat on-device

Please follow the LLM on-device deployment tutorial.

References

Community

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