Update README.md

README.md

@@ -25,22 +25,28 @@ datasets:
 
 # Use The Model
 
-####from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
 Load the tokenizer and model
+
 tokenizer = AutoTokenizer.from_pretrained("Dragneel/Phi-3-mini-Nepali-Text-Summarization-f16")
+
 model = AutoModelForCausalLM.from_pretrained("Dragneel/Phi-3-mini-Nepali-Text-Summarization-f16")
 
 Example input text
+
 input_text = "काठमाडौंको बहिराव बसपार्कमा एक भयानक दुर्घटना घटेको थियो। रातको समय थियो र भारी बर्फ जम्मा भएको थियो।"
 
 Tokenize the input text
+
 input_ids = tokenizer.encode(input_text, return_tensors='pt')
 
 Generate text with adjusted parameters
+
 outputs = model.generate(input_ids, max_new_tokens=50)
 
 Decode the generated tokens
+
 generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
 print(generated_text)