---
library_name: pytorch
license: other
pipeline_tag: text-generation
tags:
- llm
- generative_ai
- quantized
- android

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/indus_1b_quantized/web-assets/model_demo.png)

# IndusQ-1.1B: Optimized for Mobile Deployment
## State-of-the-art large language model useful on a variety of language understanding and generation tasks


Indus is today a 1.2 billion parameter model and has been supervised fine tuned for Hindi and dialects.

This model is an implementation of IndusQ-1.1B found [here](https://huggingface.co/nickmalhotra/ProjectIndus).


More details on model performance accross various devices, can be found [here](https://aihub.qualcomm.com/models/indus_1b_quantized).

### Model Details

- **Model Type:** Text generation
- **Model Stats:**
  - Input sequence length for Prompt Processor: 128
  - Max context length: 1024
  - Number of parameters: 1B
  - Precision: w4a16 + w8a16 (few layers)
  - Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations.
  - Minimum QNN SDK version required: 2.27.7
  - Supported languages: Hindi and English.
  - TTFT: Time To First Token is the time it takes to generate the first response token. This is expressed as a range because it varies based on the length of the prompt. The lower bound is for a short prompt (up to 128 tokens, i.e., one iteration of the prompt processor) and the upper bound is for a prompt using the full context length (1024 tokens).
  - Response Rate: Rate of response generation after the first response token.

| Model | Device | Chipset | Target Runtime | Response Rate (tokens per second) | Time To First Token (range, seconds)
|---|---|---|---|---|---|
| IndusQ-1.1B | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 74.6 | 0.028561 - 0.228489 | -- | -- |

## Deploying IndusQ-1.1B on-device

Please follow the [LLM on-device deployment]({genie_url}) tutorial.




## References
* [Project Indus: A Foundational Model for Indian Languages](https://www.techmahindra.com/makers-lab/indus-project/)
* [Source Model Implementation](https://huggingface.co/nickmalhotra/ProjectIndus)



## Community
* Join [our AI Hub Slack community](https://qualcomm-ai-hub.slack.com/join/shared_invite/zt-2d5zsmas3-Sj0Q9TzslueCjS31eXG2UA#/shared-invite/email) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).

## Usage and Limitations

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