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README.md

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 # Foundation Model Stack
 
-Foundation Model Stack (fms) is a collection of components for development, inference, training, and tuning of foundation models leveraging PyTorch native components. 
-For inference optimizations we aim to support PyTorch compile, accelerated transformers, and tensor parallelism. 
-At training time we aim to support FSDP, accelerated transformers, and PyTorch compile.
+Foundation Model Stack (fms) is a collection of components developed out of IBM Research used for development, inference, training, and tuning of foundation models leveraging PyTorch native components. 
+
+## Optimizations
+
+In FMS, we aim to bring the latest optimizations for pre-training/inference/fine-tuning to all of our models. A few of these optimizations include, but are not limited to:
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+- fully compileable models with no graph breaks
+- full tensor-parallel support for all applicable modules developed in fms
+- training scripts leveraging FSDP
+- state of the art light-weight speculators for improving inference performance
 
 ## Repositories