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license: apache-2.0 |
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inference: false |
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tags: [llmware-rag, p7, ov] |
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--- |
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# dragon-mistral-0.3-ov |
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<!-- Provide a quick summary of what the model is/does. --> |
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**bling-tiny-llama-ov** is an OpenVino int4 quantized version of BLING Tiny-Llama 1B, providing a very fast, very small inference implementation, optimized for AI PCs using Intel GPU, CPU and NPU. |
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[**bling-tiny-llama**](https://huggingface.co/llmware/bling-tiny-llama-v0) is a fact-based question-answering model, optimized for complex business documents. |
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Get started right away with [OpenVino](https://github.com/openvinotoolkit/openvino) |
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Looking for AI PC solutions and demos, contact us at [llmware](https://www.llmware.ai) |
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### Model Description |
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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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- **Model Parent:** 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 |
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- **RAG Benchmark Accuracy Score:** 86.5 |
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- **Quantization:** int4 |
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## Model Card Contact |
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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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