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README.md
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@@ -153,10 +153,9 @@ GRAG-PHI-SFT, running on NVIDIA A100 with 8 GPUs for 5 days, has an approximate
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It's important to note that the actual power consumption may vary depending on the specific workload and operational conditions. For accurate power consumption measurements, using dedicated power monitoring tools is recommended.
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## Bias, Risks, and Limitations
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Like any base language model or fine-tuned model without safety filtering, it is relatively easy for a user to prompt these models to generate harmful and generally sensitive content.
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It's important to note that the actual power consumption may vary depending on the specific workload and operational conditions. For accurate power consumption measurements, using dedicated power monitoring tools is recommended.
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| Model | GPU Type | Power Consumption From GPUs |
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|----------------|---------------------|-----------------------------|
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| GRAG-PHI-SFT | A100 ([Hessen AI supercomputer](https://hessian.ai/de/)) | 0.288 MWh |
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## Bias, Risks, and Limitations
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Like any base language model or fine-tuned model without safety filtering, it is relatively easy for a user to prompt these models to generate harmful and generally sensitive content.
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