Update README.md

README.md

@@ -43,8 +43,42 @@ NeXGen can be directly employed for:
 
 ## Getting Started
 
-To use NeXGen, follow these steps:
-
+To download NeXGen use this code:
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Specify the model name from Hugging Face Model Hub
+model_name = "Sirclavin/NeXGen-based"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def generate_text(prompt, max_length=100, num_beams=5, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+    # Ensure attention_mask is provided
+    attention_mask = input_ids.ne(tokenizer.pad_token_id).float()
+
+    # Generate output text
+    output = model.generate(
+        input_ids,
+        max_length=max_length,
+        num_beams=num_beams,
+        no_repeat_ngram_size=no_repeat_ngram_size,
+        top_k=top_k,
+        top_p=top_p,
+        temperature=temperature,
+        attention_mask=attention_mask  # Pass attention_mask to the generation method
+    )
+
+    decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
+    return decoded_output
+
+# Example usage:
+prompt = "Your prompt here"
+generated_text = generate_text(prompt, max_length=200)
+
+print("Generated Text:")
+print(generated_text)