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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ inference: false
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+ base_model: llmware/bling-tiny-llama-v0
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+ base_model_relation: quantized
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+ tags: [green, llmware-rag, p1, ov]
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+ ---
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+
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+ # bling-tiny-llama-onnx
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+
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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, quantized and packaged in ONNX int4 for AI PCs using Intel GPU, CPU and NPU.
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+
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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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+
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+ ### Model Description
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+
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+ - **Developed by:** llmware
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+ - **Model type:** tinyllama
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+ - **Parameters:** 1.1 billion
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+ - **Quantization:** int4
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+ - **Model Parent:** [llmware/bling-tiny-llama-v0](https://www.huggingface.co/llmware/bling-tiny-llama-v0)
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+ - **Language(s) (NLP):** English
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+ - **License:** Apache 2.0
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+ - **Uses:** Fact-based question-answering, RAG
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+ - **RAG Benchmark Accuracy Score:** 86.5
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+
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+
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+ ## Model Card Contact
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+ [llmware on github](https://www.github.com/llmware-ai/llmware)
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+ [llmware on hf](https://www.huggingface.co/llmware)
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+ [llmware website](https://www.llmware.ai)
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