Update README.md

README.md

@@ -60,22 +60,16 @@ Significantly, the **Ganga-1B** model outperforms existing open-source models th
 Use the code below to get started with the model.
 
 ```python
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer
     
 tokenizer = AutoTokenizer.from_pretrained("LingoIITGN/ganga-1b")
-model = AutoModelForCausalLM.from_pretrained(
-    "LingoIITGN/ganga-1b",
-    device_map="auto"
-)
-
-pipe = pipeline(task="text-generation", 
-                model=model, 
-                tokenizer=tokenizer,
-                max_new_tokens = 5, 
-                temperature = 0.70,
-               )
-result = pipe("2007 टूर्नामेंट में क्रिकट विश्व कप के लिए टिकटों से सबसे ज्यादा आमदनी हुई ", pad_token_id=pipe.tokenizer.eos_token_id)
-print(result)
+model = AutoModelForCausalLM.from_pretrained("LingoIITGN/ganga-1b", device_map="auto")
+
+input_text = "BCCI ने टी-20 वर्ल्ड कप के बीच जिम्बाब्वे सीरीज "
+input_ids = tokenizer.encode(input_text, return_tensors="pt").to("cuda")
+
+outputs = model.generate(input_ids, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95, temperature=0.7)
+print(tokenizer.decode(outputs[0]))
 
 ```