Update README.md

README.md

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 # Dataset Card for NIT Dataset
 
-The Network Intent Translations (NIT) dataset is a specialized dataset for translating descriptive networking scenarios into low-level deployable configurations. The NIT is intended for network intent translations in Intent-Based Networking (IBN). The dataset includes network configuration tasks in natural language (network intents) and their corresponding low-level configurations for Juniper EX3300 switches with JUNOS Base OS boot [12.3R12-S12]. 
+The Network Intent Translations (NIT) dataset is specialized for translating descriptive networking scenarios into low-level deployable configurations. The NIT is intended for network intent translations in Intent-Based Networking (IBN). The dataset includes network configuration tasks in natural language (network intents) and their corresponding low-level configurations for Juniper EX3300 switches with JUNOS Base OS boot [12.3R12-S12]. 
 
 
 ## Dataset Details
+The NIT dataset covers various networking tasks implemented on the Juniper EX3300 switch. The distribution of the commands used to implement the networking tasks is as follows:
 
-The distribution of the commands in the dataset:
 - set commands:  582 
 - show commands:  249 
 - delete commands:  73 
@@ -83,13 +83,13 @@ The distribution of the commands in the dataset:
 - monitor [3]
 
 
-### Dataset Description
+## Dataset Description
 
 
 
 
 
-### Dataset Sources 
+## Dataset Sources 
 
 
 
@@ -97,13 +97,13 @@ The distribution of the commands in the dataset:
 
 
 
-### Direct Use
+## Direct Use
 The NIT dataset can be utilized for parameter-efficient fine-tuning (PEFT) of large language models (LLMs) to translate network intent into low-level, deployable command-line configurations
 
 
 
 
-### Out-of-Scope Use
+## Out-of-Scope Use
 
 The dataset focuses solely on translating high-level network intent into command-line configurations. It does not aim to verify the accuracy of parameter values within the prompts or address any conflict detection or resolution. However, all parameter values in the dataset are valid for their respective tasks.