updated readme.md

README.md

@@ -51,16 +51,35 @@ The model is trained on English and a diverse set of Indic languages, including
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_name = "Rta-AILabs/Nandi-150M"
-
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-
-prompt = "Explain transformer in simple words."
-inputs = tokenizer(prompt, return_tensors="pt")
-
-outputs = model.generate(**inputs, max_new_tokens=100)
-print(tokenizer.decode(outputs[0]))
+model_name = "Rta-AILabs/Nandi-mini-150M"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    trust_remote_code=True,
+    device_map="auto",          
+    torch_dtype=torch.bfloat16
+)
+
+prompt = "Newton's Second Law"
+inputs = tokenizer.encode(prompt, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    inputs,
+    max_new_tokens=200,
+    do_sample=True,
+    temperature=0.3,      
+    top_k=20,
+    top_p=0.95
+)
+
+response = tokenizer.decode(
+    outputs[0],
+    skip_special_tokens=True,
+)
+
+print(response)
 ```
 
 ## 📝 Upcoming Releases & Roadmap