Update README.md

README.md

@@ -37,7 +37,7 @@ It achieves an average score of 84.29 on the [OpenLLM](https://huggingface.co/sp
 
 ### Model Optimizations
 
-This model was obtained by quantizing the weights and activations of [Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct) to FP8 data type, ready for inference with vLLM built from source.
+This model was obtained by quantizing the weights and activations of [Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct) to FP8 data type.
 This optimization reduces the number of bits per parameter from 16 to 8, reducing the disk size and GPU memory requirements by approximately 50%.
 
 Only the weights and activations of the linear operators within transformers blocks are quantized. Symmetric per-tensor quantization is applied, in which a single linear scaling maps the FP8 representations of the quantized weights and activations.