Update README.md

README.md

@@ -30,4 +30,26 @@ As the model is untrained, it has not been evaluated on any benchmark datasets.
 
 Limitations
 Untrained: The model is untrained and will not perform well on any task until it has been fine-tuned.
-Ethical Considerations: Users should be mindful of the ethical implications of deploying fine-tuned models, especially in sensitive applications.
+Ethical Considerations: Users should be mindful of the ethical implications of deploying fine-tuned models, especially in sensitive applications.
+
+
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the fine-tuned model and tokenizer
+model = AutoModelForCausalLM.from_pretrained("oktrained/llama3.1_180M_untrained")
+tokenizer = AutoTokenizer.from_pretrained("oktrained/llama3.1_180M_untrained")
+
+# Sample input text
+input_text = "Once upon a time"
+
+# Tokenize input
+inputs = tokenizer(input_text, return_tensors="pt")
+
+# Generate output
+output = model.generate(**inputs, max_length=50)
+
+# Decode output
+generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+print(generated_text)