[Minor] Update README.md

tinychat/README.md

@@ -44,7 +44,7 @@ Thanks to AWQ, TinyChat can now deliver more prompt responses through 4-bit infe
 
 We benchmark TinyChat on A6000 (server-class GPU), 4090 (desktop GPU) and Orin (edge GPU).
 
-We use the default implementation from Huggingface for the FP16 baseline. The INT4 implementation applies AWQ and utilizes our fast W4A16 GPU kernel. Please notice that the end-to-end runtime for INT4 TinyChat could be further improved if we reduce the framework overhead from Huggingface (e.g. utilizing the implementation from TGI). 
+We use the default implementation from Huggingface for the FP16 baseline. The INT4 implementation applies AWQ and utilizes our fast W4A16 GPU kernel. Please notice that the end-to-end runtime for INT4 TinyChat could be further improved if we reduce the framework overhead from Huggingface (e.g. utilizing the implementation from TGI). We are working on a new release with even faster inference performance, please stay tuned!
 
 The latency reported in all tables are per-token latency for the generation stage.