Updated index

Author: madeline-underwood

content/learning-paths/servers-and-cloud-computing/distributed-inference-with-llama-cpp/_index.md

@@ -1,23 +1,19 @@
 ---
 title: Distributed inference using llama.cpp
 
-draft: true
-cascade:
-    draft: true
-    
 minutes_to_complete: 30
 
-who_is_this_for: This learning path is for developers with some experience using llama.cpp who want to learn about distributed inference.
+who_is_this_for: This Learning Path is for developers with some experience using llama.cpp who want to learn distributed inference.
 
 learning_objectives: 
-    - Set up the main host and worker nodes using llama.cpp
-    - Run a large quantized model (e.g., Llama 3.1 405B) on CPUs in a distributed manner on Arm machines
+    - Set up a main host and worker nodes with llama.cpp
+    - Run a large quantized model (for example, Llama 3.1 405B) with distributed CPU inference on Arm machines
 
 prerequisites:
-    - Three AWS c8g.16xlarge instances with at least 2TB EBS space.
-    - Python installed on the AWS instances.
-    - Access to Meta’s gated repository for the Llama 3.1 model family, with a Hugging Face token generated for downloading the models.
-    - Familiarity with -> [Deploy a Large Language Model (LLM) chatbot with llama.cpp using KleidiAI on Arm servers](/learning-paths/servers-and-cloud-computing/llama-cpu)
+    - Three AWS c8g.16xlarge instances with at least 2 TB of EBS storage
+    - Python 3 installed on each instance
+    - Access to Meta's gated repository for the Llama 3.1 model family and a Hugging Face token to download models
+    - Familiarity with [Deploy a Large Language Model (LLM) chatbot with llama.cpp using KleidiAI on Arm servers](/learning-paths/servers-and-cloud-computing/llama-cpu)
     - Familiarity with AWS
 
 author: Aryan Bhusari
@@ -38,7 +34,7 @@ operatingsystems:
 
 further_reading:
     - resource:
-        title: Llama.cpp rpc-server code
+        title: llama.cpp RPC server code
         link: https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc
         type: Code