Update model name

Signed-off-by: Prasoon Varshney <[email protected]>

README.md

@@ -15,13 +15,13 @@ library_name: peft
 # Model Overview
 ## Description:
 
-**Llama-3.1-NemoGuard-8B-Topic-Control** can be used for topical and dialogue moderation of user prompts in human-assistant interactions being designed for task-oriented dialogue agents and custom policy-based moderation. 
+**Llama Nemotron Topic Guard V1**, formerly known as **Llama-3.1-NemoGuard-8B-Topic-Control**, can be used for topical and dialogue moderation of user prompts in human-assistant interactions being designed for task-oriented dialogue agents and custom policy-based moderation. 
 
-Try out the model here: [Llama-3.1-NemoGuard-8B-Topic-Control](https://build.nvidia.com/nvidia/llama-3_1-nemoguard-8b-topic-control)
+Try out the model here: [Llama-3.1-Nemotron-Topic-Guard-8B-v1](https://build.nvidia.com/nvidia/llama-3_1-nemoguard-8b-topic-control)
 
 Given a system instruction (also called topical instruction, i.e. specifying which topics are allowed and disallowed) and a conversation history ending with the last user prompt, the model returns a binary response that flags if the user message respects the system instruction, (i.e. message is on-topic or a distractor/off-topic). 
 
-The base large language model (LLM) is the multilingual [Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) model from Meta. Llama-3.1-TopicGuard is LoRa-tuned on a topic-following dataset generated synthetically with [Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1).
+The base large language model (LLM) is the multilingual [Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) model from Meta. Llama Nemotron Topic Guard V1 is LoRa-tuned on a topic-following dataset generated synthetically with [Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1).
 This model is ready for commercial use.  <br>
 
 ### License/Terms of Use:
@@ -44,7 +44,7 @@ Related paper:
 
 ## Using the Model
 
-Llama 3.1 NemoGuard 8B TopicControl performs input moderation, such as ensuring that the user prompt is consistent with rules specified as part of the system prompt.
+Llama-3.1-Nemotron-Topic-Guard-8B-v1 performs input moderation, such as ensuring that the user prompt is consistent with rules specified as part of the system prompt.
 
 The prompt template consists of two key sections: system instruction and conversation history that includes a sequence of user prompts and LLM responses. Typically, the prompt concludes with the current user query.
 
@@ -103,9 +103,9 @@ The topic control model responds to the final user prompt with a response like `
 
 ## Integrating with NeMo Guardrails
 
-To integrate the topic control model with NeMo Guardrails, you would need access to the NVIDIA NIM container for llama-3.1-nemoguard-8b-topic-control. More information about the NIM container can be found [here](https://docs.nvidia.com/nim/#nemoguard).
+To integrate the topic control model with NeMo Guardrails, you would need access to the NVIDIA NIM container for llama-3.1-nemotron-topic-guard-8b-v1. More information about the NIM container can be found [here](https://docs.nvidia.com/nim/llama-3-1-nemoguard-8b-topiccontrol/latest/getting-started.html).
 
-NeMo Guardrails uses the LangChain ChatNVIDIA connector to connect to a locally running NIM microservice like llama-3.1-nemoguard-8b-topic-control.
+NeMo Guardrails uses the LangChain ChatNVIDIA connector to connect to a locally running NIM microservice like llama-3.1-nemotron-topic-guard-8b-v1.
 The topic control microservice exposes the standard OpenAI interface on the `v1/completions` and `v1/chat/completions` endpoints.
 
 NeMo Guardrails simplifies the complexity of building the prompt template, parsing the topic control model responses, and provides a programmable method to build a chatbot with content safety rails.
@@ -123,7 +123,7 @@ models:
     engine: nim
     parameters:
       base_url: "http://localhost:8000/v1"
-      model_name: "llama-3.1-nemoguard-8b-topic-control"
+      model_name: "llama-3.1-nemotron-topic-guard-8b-v1"
 
 rails:
   input:
@@ -133,7 +133,7 @@ rails:
 
 - Field `engine` specifies `nim`.
 - Field `parameters.base_url` specifies the IP address and port of the ${__product_long_name} host.
-- Field `parameters.model_name` in the Guardrails configuration must match the model name served by the llama-3.1-nemoguard-8b-topic-control.
+- Field `parameters.model_name` in the Guardrails configuration must match the model name served by the RESTful endpoint.
 - The rails definition specifies `topic_control` as the model.
 
 Refer to [NVIDIA NeMo Guardrails](https://developer.nvidia.com/docs/nemo-microservices/guardrails/source/overview.html) documentation for more information about the configuration file.
@@ -150,7 +150,7 @@ We perform Parameter Efficient FineTuning (PEFT) over the base model using the f
 
 **Training Method:**
 
-The training method for **Llama-3.1-TopicGuard** involves the following concepts:
+The training method for **Llama-3.1-Nemotron-Topic-Guard-8B-v1** involves the following concepts:
 - A system instruction which acts like a topical instruction with the rules that define the context of the user-assistant interaction, i.e. topics allowed or disallowed by the current task-oriented scenario, conversation style and tone, conversation flows.
 - Any user message in the conversation that respects the topical instruction is considered on-topic, while a user message that contradicts at least one of the rules is a distractor or off-topic.
 - A synthetic generated dataset, called CantTalkAboutThis-Mixtral-1.0, of approximately 1,000 multi-turn conversations is used to instruction-tune the base model. Each conversation has a specific topical instruction from various broad domains (i.e. customer support, travel, legal) and contains an entire conversation which is on-topic, together with several distractor user messages replacing some of the on-topic ones at specific key points in the conversation. 
@@ -228,7 +228,7 @@ off-topic
 **Preferred/Supported Operating System(s):** Linux (Ubuntu) <br>
 
 ## Model Version(s): 
-Llama-3.1-TopicGuard  <br>
+Llama-3.1-Nemotron-Topic-Guard-8B-v1  <br>
 
 # Training, Testing, and Evaluation Datasets: