chore: more info

README.md

@@ -10,3 +10,23 @@ widget:
 # code-gemma
 
 Google's `gemma-2b-it` trained `code_instructions_122k_alpaca_style` dataset
+
+# Usage
+
+```py
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="gnumanth/code-gemma")
+```
+
+
+```
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("gnumanth/code-gemma")
+model = AutoModelForCausalLM.from_pretrained("gnumanth/code-gemma")
+```
+
+[Hemanth HM](https://h3manth.com)