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llmware
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bling-phi-3

Text Generation
Transformers
PyTorch
phi3
conversational
custom_code
text-generation-inference
Model card Files Community
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@@ -25,7 +25,9 @@ Evaluated against the benchmark test: [RAG-Instruct-Benchmark-Tester](https://
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  For test run results (and good indicator of target use cases), please see the files ("core_rag_test" and "answer_sheet" in this repo).
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- Note: compare results with [bling-phi-2](https://www.huggingface.co/llmware/bling-phi-2-v0), and [dragon-mistral-7b](https://www.huggingface.co/llmware/dragon-mistral-7b-v0). See also [bling-phi-3-gguf](https://www.huggingface.co/llmware/bling-phi-3-gguf).
 
 
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  Note: the Pytorch version answered 1 question with "Not Found" while the quantized version answered it correctly, hence the small difference in scores.
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  For test run results (and good indicator of target use cases), please see the files ("core_rag_test" and "answer_sheet" in this repo).
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+ Note: compare results with [bling-phi-2](https://www.huggingface.co/llmware/bling-phi-2-v0), and [dragon-mistral-7b](https://www.huggingface.co/llmware/dragon-mistral-7b-v0).
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+ Note: see also the quantized gguf version of the model- [bling-phi-3-gguf](https://www.huggingface.co/llmware/bling-phi-3-gguf).
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  Note: the Pytorch version answered 1 question with "Not Found" while the quantized version answered it correctly, hence the small difference in scores.
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