Update README.md

Author: aarora79

recipes/benchmarks/fmbench/README.md

@@ -4,7 +4,7 @@ The [`FMBench`](https://github.com/aws-samples/foundation-model-benchmarking-too
 
 ## The need for benchmarking
 
-Customers often wonder what is the best AWS service to run Llama models for _my specific use-case_ and _my specific price performance requirements_. While model evaluation metrics are available on several leaderboards ([`HELM`](https://crfm.stanford.edu/helm/lite/latest/#/leaderboard), [`LMSys`](https://chat.lmsys.org/?leaderboard)), but the price performance comparison can be notoriously hard to find and even more harder to trust. In such a scenario, we think it is best to be able to run performance benchmarking yourself on either on your own dataset or on a similar (task wise, prompt size wise) open-source dataset ([`LongBench`](https://huggingface.co/datasets/THUDM/LongBench)), [`QMSum`](https://paperswithcode.com/dataset/qmsum). This is the problem that [`FMBench`](https://github.com/aws-samples/foundation-model-benchmarking-tool/tree/main) solves.
+Customers often wonder what is the best AWS service to run Llama models for _my specific use-case_ and _my specific price performance requirements_. While model evaluation metrics are available on several leaderboards ([`HELM`](https://crfm.stanford.edu/helm/lite/latest/#/leaderboard), [`LMSys`](https://chat.lmsys.org/?leaderboard)), but the price performance comparison can be notoriously hard to find and even more harder to trust. In such a scenario, we think it is best to be able to run performance benchmarking yourself on either on your own dataset or on a similar (task wise, prompt size wise) open-source dataset ([`LongBench`](https://huggingface.co/datasets/THUDM/LongBench), [`QMSum`](https://paperswithcode.com/dataset/qmsum)). This is the problem that [`FMBench`](https://github.com/aws-samples/foundation-model-benchmarking-tool/tree/main) solves.
 
 ## [`FMBench`](https://github.com/aws-samples/foundation-model-benchmarking-tool/tree/main): an open-source Python package for FM benchmarking on AWS
 
@@ -376,4 +376,4 @@ The Llama2-13b-chat and Llama2-70b-chat models are available on [Bedrock](https:
 
 ## More..
 
-For bug reports, enhancement requests and any questions please create a [GitHub issue](https://github.com/aws-samples/foundation-model-benchmarking-tool/issues) on the `FMBench` repo.
+For bug reports, enhancement requests and any questions please create a [GitHub issue](https://github.com/aws-samples/foundation-model-benchmarking-tool/issues) on the `FMBench` repo.