Update README.md

Add Supported Trainers section - Axolotl and Example Trainer subsections

README.md

@@ -211,6 +211,29 @@ Environments come with detailed logging and reporting support, runs track comple
 
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+# Trainer Integrations
+## Axolotl
+<a href="https://github.com/axolotl-ai-cloud/plugin-atropos">
+  <img
+    src="https://github.com/user-attachments/assets/be629253-a8b1-4354-b6da-5e404e9c854d"
+    alt="Atropos plugin logo"
+    width="50%">
+</a>
+
+Axolotl is a powerful tool for fine-tuning a wide range of AI models, supporting techniques like LoRA and QLoRA through simple YAML configurations.
+
+The [Atropos plugin for Axolotl](https://github.com/axolotl-ai-cloud/plugin-atropos) seamlessly integrates Atropos' RL environments into Axolotl's training pipelines.
+This allows you to leverage Atropos for reinforcement learning while utilizing Axolotl's extensive features for model fine-tuning.
+
+To use, follow the readme on the [plugin repository](https://github.com/axolotl-ai-cloud/plugin-atropos).
+
+## Atropos' Example Trainer
+Atropos repo contains an example trainer that should primarily be used as a reference example to show how a trainer and inference provider can be integrated with Atropos to complete the RL Training Loop.
+
+To use the example trainer, see this page: [training example guide](example_trainer/README.md)
+
+---
+
 ## Testing and Debugging Tools
 
 The trajectory-handler provides several debugging tools to help environment developers test and understand their environments locally without requiring the full distributed infrastructure.