Updated README

README.md

@@ -23,7 +23,7 @@ Please refer to the AWQ quantization license ([link](https://github.com/llm-awq/
 
 ## CUDA Version
 
-This model was successfully tested on CUDA driver v530.30.02 and runtime v11.7 with Python v3.10.11. Please note that AWQ requires NVIDIA GPUs with compute capability of 80 or higher.
+This model was successfully tested on CUDA driver v530.30.02 and runtime v11.7 with Python v3.10.11. Please note that AWQ requires NVIDIA GPUs with compute capability of `8.0` or higher.
 
 For Docker users, the `nvcr.io/nvidia/pytorch:23.06-py3` image is runtime v12.1 but otherwise the same as the configuration above and has also been verified to work.
 
@@ -84,7 +84,7 @@ output = model.generate(
     repetition_penalty=1.1,
     eos_token_id=tokenizer.eos_token_id
 )
-print(tokenizer.decode(output[0], skip_special_tokens=True))
+# print(tokenizer.decode(output[0], skip_special_tokens=True))
 ```
 
 ## Evaluation