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@@ -20,8 +20,9 @@ Here we discuss frequently asked questions that may occur and we found useful al
 
 5. What are the hardware SKU requirements for deploying these models?
 
-    Hardware requirements vary based on latency, throughput and cost constraints. For good latency, the models were split across multiple GPUs with tensor parallelism in a machine with NVIDIA A100s or H100s. But TPUs, other types of GPUs, or even commodity hardware can also be used to deploy these models (e.g. https://github.com/ggerganov/llama.cpp).
+    Hardware requirements vary based on latency, throughput and cost constraints. For good latency, the models were split across multiple GPUs with tensor parallelism in a machine with NVIDIA A100s or H100s. But TPUs, other types of GPUs like A10G, T4, L4, or even commodity hardware can also be used to deploy these models (e.g. https://github.com/ggerganov/llama.cpp).
+    If working on a CPU, it is worth looking at this [blog post](https://www.intel.com/content/www/us/en/developer/articles/news/llama2.html) from Intel for an idea of Llama 2's performance on a CPU.
 
 6. What are the hardware SKU requirements for fine-tuning Llama pre-trained models?
 
-    Fine-tuning requirements vary based on amount of data, time to complete fine-tuning and cost constraints. To fine-tune these models we have generally used multiple NVIDIA A100 machines with data parallelism across nodes and a mix of data and tensor parallelism intra node. But using a single machine, or other GPU types are definitely possible (e.g. alpaca models are trained on a single RTX4090: https://github.com/tloen/alpaca-lora).
+    Fine-tuning requirements vary based on amount of data, time to complete fine-tuning and cost constraints. To fine-tune these models we have generally used multiple NVIDIA A100 machines with data parallelism across nodes and a mix of data and tensor parallelism intra node. But using a single machine, or other GPU types like NVIDIA A10G or H100 are definitely possible (e.g. alpaca models are trained on a single RTX4090: https://github.com/tloen/alpaca-lora).