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--- |
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base_model: |
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- ibm-granite/granite-4.0-h-350m |
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--- |
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# Granite-4.0-h-350M |
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<p align="center"> |
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<img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F6851901ea43b4824f79e27a9%2FvBAkkCukOQ3CHlT2GBwvI.png%26quot%3B%3C%2Fspan%3E width="350" height="350"> |
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</p> |
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Run **Granite-4.0-h-350M** optimized for **Qualcomm Hexagon NPUs** with [NexaSDK](https://sdk.nexa.ai) on Android |
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## Model Description |
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**Granite-4.0-h-350M** is a 350-million-parameter transformer model from IBM’s Granite 4.0 family — designed for efficient inference, low-latency edge deployment, and instruction following at compact scale. |
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It shares the same data quality, architecture design, and alignment pipeline as larger Granite 4.0 models but is optimized for lightweight environments where performance per watt and model size are critical. |
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Built on the **Granite 4.0** foundation, this model continues IBM’s commitment to open, responsible AI, offering transparency and adaptability for developers, researchers, and embedded AI applications. |
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## Features |
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- **Compact yet capable**: Delivers high-quality generation and reasoning with just 350M parameters. |
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- **Instruction-tuned**: Follows natural language instructions for diverse tasks. |
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- **Low-latency performance**: Ideal for CPU, GPU, and NPU inference. |
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- **Efficient deployment**: Runs smoothly on edge and resource-constrained devices. |
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- **Open and transparent**: Released under IBM’s open model governance framework. |
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## Use Cases |
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- On-device assistants and chatbots |
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- Edge AI and IoT inference |
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- Document and text summarization |
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- Education and lightweight reasoning tasks |
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- Prototype fine-tuning for domain adaptation |
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## Inputs and Outputs |
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**Input**: |
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- Text prompt (instruction or question) |
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**Output**: |
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- Generated text response completing or following the input prompt |
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## License |
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This model is released under the **Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0)** license. |
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Non-commercial use, modification, and redistribution are permitted with attribution. |
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For commercial licensing, please contact **[email protected]**. |
