Update README.md

README.md

@@ -29,4 +29,46 @@ The dataset is structured hierarchically, with each level representing an increa
 4. **Sub-Unit:** Combination of two or more fragments.
 5. **Unit:** Combination of two or more sub-units.
 6. **Super-Unit:** Combination of two or more units.
-7. **Mega-Unit:** Combination of two or more super-units.
+7. **Mega-Unit:** Combination of two or more super-units.
+
+**How to Use**
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from IPython.display import display, HTML
+
+# prompt: load model and generate example
+model_name = "nqzfaizal77ai/sa-145m-en-wikipedia-culture-part1-1bc"
+
+model = AutoModelForCausalLM.from_pretrained(model_name,trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(model_name,trust_remote_code=True)
+
+torch.manual_seed(3077)
+
+# Example usage stochastic decode
+input_text = "The cultural impact of the internet is"
+inputs = tokenizer(input_text, return_tensors="pt")
+output = model.generate(**inputs,
+                          do_sample=True,
+                          top_k=50,
+                          top_p=0.95,
+                          repetition_penalty=1.2,
+                          max_length=100)
+def print_with_border(text):
+  """Prints the given text with a border around it."""
+  display(HTML(f"<div style='border: 1px solid black; padding: 10px;'>{text}</div>"))
+
+# Example usage greedy decode
+print_with_border(tokenizer.decode(output[0], skip_special_tokens=True))
+
+output = merged_model.generate(**inputs,
+                          do_sample=False,
+                          max_length=100)
+def print_with_border(text):
+  """Prints the given text with a border around it."""
+  display(HTML(f"<div style='border: 1px solid black; padding: 10px;'>{text}</div>"))
+
+# Example usage
+print_with_border(tokenizer.decode(output[0], skip_special_tokens=True))
+```