Update README.md

README.md

@@ -108,21 +108,18 @@ print(tokenizer.decode(outputs[0]))
 
 ### EXAMPLE: USE CASES
 
--MICROD v1 may not rival larger models in breadth, its focus on accessible, browser-based AI development opens doors for 
-innovators balancing all perspectives in the SLM space, from efficiency advocates to those cautious about over-reliance 
-on black-box systems.
-
-Scenario,Steps,Tools Needed,Potential Outcomes
-Basic Text Generation,"1. Install Transformers library
-2. Load model/tokenizer
-3. Generate from prompt","Python, Hugging Face",Simple stories or responses; experiment with max_length
-Custom Agent Development,"1. Use Micro Distillery app
-2. Initialize GRPO
-3. Train on custom data
-4. Export to ONNX","Browser, webXOS PWA",AI agents for games or prompts; test GRPO groups
-Educational Fine-Tuning,"1. Prepare dataset
-2. Fine-tune via GRPO Trainer
-3. Evaluate in sandbox","Hugging Face, Python sandbox",Learn RLHF; create task-specific variants like code tutors
-Offline Simulation,"1. Install as PWA
-2. Run training terminal
-3. Monitor VAE masking",Mobile/browser,Prototype without internet; export for deployment
+**MICROD_v1** may not rival larger models in breadth, but its focus on accessibility and browser-based AI development opens doors for 
+innovators balancing all perspectives in the Small Language Model space.
+
+1. Prototype without Internet
+2. Offline Simulations in Black Box
+3. Simple Story Generators
+4. Custom Agentic Development
+5. Train on Custom Data
+6. Experiment with max_length
+7. AI agents for custom Games
+8. Educational Fine-Tuning
+9. Prepare Datasets
+10. Fine-tune via GRPO Trainer 
+11. Evaluate PY in Sandbox
+12. Create task-specific Variants like Code Tutors