Update README.md

README.md

@@ -1,7 +1,8 @@
 ---
 license: apache-2.0
 datasets:
-- bravesoftware/androcles-2-chat-50k
+- bravesoftware/diverse-llm-prompts-34k
+- lmsys/lmsys-chat-1m
 base_model:
 - answerdotai/ModernBERT-base
 ---
@@ -40,15 +41,15 @@ Androcles is our inhouse **Prompt Classification Model**, used to classify user
 
 ## Training
 
-Androcles 2 was trained using https://huggingface.co/datasets/bravesoftware/androcles-2-chat-50k
+Androcles 2 was trained using a mix of https://huggingface.co/datasets/bravesoftware/diverse-llm-prompts-34k & https://huggingface.co/datasets/lmsys/lmsys-chat-1m
 
-The scripts for training the model & generating the initial dataset can be found here [TBA]
+The scripts for training the model & generating the initial dataset can be found [here](https://github.com/brave/Androcles/tree/main)
 
 ## How We Use It
 
 We use Androcles in a couple of different ways:
 
-* As a first step in our Leo backend server [TBA], classifying prompts into categories with the aim of dynamically changing available tools/instructions depending on what the user asks for - See here [tba]
+* As a first step in our (AI Gateway Server)[https://github.com/brave/ai-gateway/tree/main] powering [Leo](https://brave.com/leo/), classifying prompts into categories with the aim of dynamically changing available tools/instructions depending on what the user asks for - See here [tba]
 * As a 'primary category' labeller for our privacy-preserving Leo Analytics server
 
 We host it using Nvidia's Triton Inference Server to serve it with low-latency at scale, but we've also used KServe in the past