v0.57.0
Browse files- LICENSE +1 -0
- README.md +120 -0
- release_assets.json +12 -0
LICENSE
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The license of the original trained model can be found at https://huggingface.co/microsoft/Phi-4-mini-instruct/blob/main/LICENSE.
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README.md
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---
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library_name: pytorch
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license: other
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tags:
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- llm
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- generative_ai
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- android
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pipeline_tag: text-generation
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---
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# Phi-4-Mini-Instruct: Optimized for Qualcomm Devices
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Phi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data.
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This is based on the implementation of Phi-4-Mini-Instruct found [here](https://huggingface.co/microsoft/Phi-4-mini-instruct).
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This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.57.0/src/qai_hub_models/models/phi_4_mini_instruct) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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## Deploying Phi-4-Mini-Instruct on-device
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Follow the [GenieX quickstart](https://geniex.aihub.qualcomm.com/en/get-started/quickstart) to install GenieX and deploy the model on a target device.
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## Getting Started
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There are two ways to deploy this model on your device:
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### Option 1: Download Pre-Exported Models
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Below are pre-exported model assets ready for deployment.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| GENIEX_LLAMACPP | q4_0 | Universal | | [Download](https://huggingface.co/bartowski/microsoft_Phi-4-mini-instruct-GGUF/resolve/main/microsoft_Phi-4-mini-instruct-Q4_0.gguf)
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For more device-specific assets and performance metrics, visit **[Phi-4-Mini-Instruct on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/phi_4_mini_instruct)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.57.0/src/qai_hub_models/models/phi_4_mini_instruct) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [Phi-4-Mini-Instruct on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.57.0/src/qai_hub_models/models/phi_4_mini_instruct) for usage instructions.
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## Model Details
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**Model Type:** Model_use_case.text_generation
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**Model Stats:**
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- Number of parameters: 3.8B
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- 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 (4096 tokens).
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- Response Rate: Rate of response generation after the first response token.
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Context Length | Response Rate (tokens per second) | Time To First Token (range, seconds)
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|---|---|---|---|---|---|---
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 512 | 23.272858 | 0.92645325 - 3.705813
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 512 | 22.664968 | 1.03434575 - 4.137383
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 512 | 19.242405 | 0.17659049999999998 - 0.7063619999999999
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 4096 | 12.621046 | 2.2515993749999996 - 72.05117999999999
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 4096 | 12.03971 | 2.4794271875 - 79.34167
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Gen 5 Mobile | 4096 | 11.220493 | 0.36033615625 - 11.530757
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 512 | 24.055461 | 0.9468802500000001 - 3.7875210000000004
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 512 | 23.939526 | 0.95809125 - 3.832365
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 512 | 19.557942 | 0.1830165 - 0.732066
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 4096 | 13.965758 | 1.94027484375 - 62.088795
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 4096 | 8.177678 | 2.3551633124999998 - 75.36522599999999
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® 8 Elite Mobile | 4096 | 13.116693 | 0.35286768749999997 - 11.291765999999999
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 512 | 33.714527 | 0.24767750000000002 - 0.9907100000000001
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 512 | 33.35471 | 0.248513 - 0.994052
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 512 | 22.484254 | 0.12369325 - 0.494773
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 4096 | 24.554353 | 0.44789846875 - 14.332751
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 4096 | 24.309187 | 0.4479129375 - 14.333214
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X2 Elite | 4096 | 15.507219 | 0.19384584375 - 6.203067
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 512 | 27.988389 | 0.40832025 - 1.633281
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 512 | 27.143556 | 0.46132475 - 1.845299
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 512 | 16.042448 | 0.25184725 - 1.007389
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 4096 | 15.617096 | 0.913791375 - 29.241324
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 4096 | 16.000366 | 0.9590768749999999 - 30.690459999999998
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| Phi-4-Mini-Instruct | GENIEX_LLAMACPP | q4_0 | Snapdragon® X Elite | 4096 | 9.673267 | 0.41174053125 - 13.175697
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## License
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* The license for the original implementation of Phi-4-Mini-Instruct can be found
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[here](https://huggingface.co/microsoft/Phi-4-mini-instruct/blob/main/LICENSE).
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## References
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* [Phi-4 Technical Report](https://arxiv.org/abs/2412.08905)
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* [Source Model Implementation](https://huggingface.co/microsoft/Phi-4-mini-instruct)
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## Community
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* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
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* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).
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## Usage and Limitations
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This model may not be used for or in connection with any of the following applications:
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- Accessing essential private and public services and benefits;
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- Administration of justice and democratic processes;
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- Assessing or recognizing the emotional state of a person;
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- Biometric and biometrics-based systems, including categorization of persons based on sensitive characteristics;
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- Education and vocational training;
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- Employment and workers management;
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- Exploitation of the vulnerabilities of persons resulting in harmful behavior;
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- General purpose social scoring;
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- Law enforcement;
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- Management and operation of critical infrastructure;
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- Migration, asylum and border control management;
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- Predictive policing;
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- Real-time remote biometric identification in public spaces;
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- Recommender systems of social media platforms;
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- Scraping of facial images (from the internet or otherwise); and/or
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- Subliminal manipulation
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release_assets.json
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{
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"version": "0.57.0",
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"precisions": {
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"q4_0": {
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"universal_assets": {
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"geniex_llamacpp": {
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"download_url": "https://huggingface.co/bartowski/microsoft_Phi-4-mini-instruct-GGUF/resolve/main/microsoft_Phi-4-mini-instruct-Q4_0.gguf"
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}
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}
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}
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}
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}
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