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README.md
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@@ -12,6 +12,23 @@ BLING models are fine-tuned with distilled high-quality custom instruct datasets
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the objective of providing a high-quality Instruct model that is 'inference-ready' on a CPU laptop even
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without using any advanced quantization optimizations.
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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without the need for a lot of complex instruction verbiage - provide a text passage context, ask questions, and get clear fact-based responses.
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### Benchmark Tests
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Evaluated against the benchmark test: [RAG-Instruct-Benchmark-Tester](https://www.huggingface.co/llmware/rag_instruct_benchmark_tester)
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Average of 2 Test Runs with 1 point for correct answer, 0.5 point for partial correct or blank / NF, 0.0 points for incorrect, and -1 points for hallucinations.
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--**Accuracy Score**: **73.25** correct out of 100
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--Not Found Classification: 17.5%
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--Boolean: 29%
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--Math/Logic: 0%
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--Complex Questions (1-5): 1 (Low)
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--Summarization Quality (1-5): 1 (Coherent, extractive)
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--Hallucinations: No hallucinations observed in test runs.
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For test run results, please see the files ("core_rag_test" and "answer_sheet" in the repo).
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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the objective of providing a high-quality Instruct model that is 'inference-ready' on a CPU laptop even
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without using any advanced quantization optimizations.
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### Benchmark Tests
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Evaluated against the benchmark test: [RAG-Instruct-Benchmark-Tester](https://www.huggingface.co/datasets/llmware/rag_instruct_benchmark_tester)
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Average of 2 Test Runs with 1 point for correct answer, 0.5 point for partial correct or blank / NF, 0.0 points for incorrect, and -1 points for hallucinations.
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--**Accuracy Score**: **73.25** correct out of 100
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--Not Found Classification: 17.5%
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--Boolean: 29%
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--Math/Logic: 0%
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--Complex Questions (1-5): 1 (Low)
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--Summarization Quality (1-5): 1 (Coherent, extractive)
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--Hallucinations: No hallucinations observed in test runs.
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For test run results, please see the files ("core_rag_test" and "answer_sheet" in the repo).
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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without the need for a lot of complex instruction verbiage - provide a text passage context, ask questions, and get clear fact-based responses.
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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