Update README.md

README.md

@@ -4,19 +4,18 @@ license: llama2
 
 ## Description
 
-This model as intended to be used as an accelerator for llama 13B (chat). 
-
-It takes inspiration from the Medusa architecture and modifies the MLP into a multi-stage MLP,
-where each stage predicts a single token in the draft. Each stage takes as input both a state
-vector and sampled token embedding from the prior stage (the base model can be considered
-stage 0). The inputs are projected and passed through a LayerNorm/GeLU activation, forming a
-new state vector. This state vector is used to predict the next draft token, which, with the new
-state vector, acts as input for the next stage of prediction. We sample multiple tokens at each
-stage, and emit a tree of candidate suffixes to evaluate in parallel.
-
-
-Undlerlying implementation of Paged Attention KV-Cached and speculator can be found in https://github.com/foundation-model-stack/fms-extras
-Production implementation using `fms-extras` implementation can be found in https://github.com/tdoublep/text-generation-inference/tree/speculative-decoding
+This model is intended to be used as an accelerator for llama 13B (chat) and takes inspiration 
+from the Medusa architecture and modifies the MLP into a multi-stage MLP, where each stage predicts 
+a single token in the draft. Each stage takes as input both a state vector and sampled token embedding 
+from the prior stage (the base model can be considered stage 0). The inputs are projected and passed 
+through a LayerNorm/GeLU activation, forming a new state vector. This state vector is used to predict 
+the next draft token, which, with the new state vector, acts as input for the next stage of prediction. 
+We sample multiple tokens at each stage, and emit a tree of candidate suffixes to evaluate in parallel.
+
+## Code
+
+- Paged Attention KV-Cache / Speculator Implementations: https://github.com/foundation-model-stack/fms-extras
+- Production Server with speculative decoding implementation: https://github.com/tdoublep/text-generation-inference/tree/speculative-decoding
 
 ## Samples