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tags: [green, llmware-rag, p1, ov]
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# bling-tiny-llama-
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**bling-tiny-llama-
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This model is one of the smallest and fastest in the series. For higher accuracy, look at larger models in the BLING/DRAGON series.
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- **RAG Benchmark Accuracy Score:** 86.5
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Get started right away with [
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Looking for AI PC solutions, contact us at [llmware](https://www.llmware.ai)
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tags: [green, llmware-rag, p1, ov]
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# bling-tiny-llama-onnx
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**bling-tiny-llama-onnx** is a very small, very fast fact-based question-answering model, designed for retrieval augmented generation (RAG) with complex business documents, and quantized and packaged in ONNX int4 for AI PCs using Intel GPU, CPU and NPU.
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This model is one of the smallest and fastest in the series. For higher accuracy, look at larger models in the BLING/DRAGON series.
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- **RAG Benchmark Accuracy Score:** 86.5
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Get started right away with [ONNX Runtime](https://github.com/microsoft/onnxruntime)
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Looking for AI PC solutions, contact us at [llmware](https://www.llmware.ai)
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