Update README.md

README.md

@@ -66,9 +66,10 @@ The model can be integrated into larger systems or applications that require Eng
 
 Use the code below to get started with the model:
 
+----------------------------------------------------------------------------------------
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-# Load the model and tokenizer
+#Load the model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained("Satwik11/gemma-2b-mt-Hindi-Fintuned")
 model = AutoModelForCausalLM.from_pretrained("Satwik11/gemma-2b-mt-Hindi-Fintuned")
 
@@ -84,7 +85,7 @@ def generate_translation(prompt, max_length=90):
     
     return translated_text
 
-# Test the model with some example sentences
+#Test the model with some example sentences
 test_sentences = [
     "Today is August 19.The maximum temperature is 70 degrees Fahrenheit"
 ]
@@ -94,7 +95,7 @@ for sentence in test_sentences:
     translation = generate_translation(prompt)
     print(translation)
 
-
+-----------------------------------------------------------------------------------------------
 ## Training Details
 
 ### Training Data