Update README.md

README.md

@@ -16,4 +16,62 @@ datasets:
 ---
 
 ## Fintuned Salesforce/codet5-small base model using 1000000 rows of data with git commits of different types of random languages for 5 epochs
-## Took a total of 10 hours in a gpu of RTX 4060TI 16GB VRAM.
+## Took a total of 10 hours in a gpu of RTX 4060TI 16GB VRAM.
+## Use the below instructions for inference
+```
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+Load the correct CodeT5 tokenizer and model
+model_name = "Salesforce/codet5-small"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+#Example Git diff input
+git_diff = """
+diff --git a/example.py b/example.py
+index 3b18e12..b3f7e54 100644
+--- a/example.py
++++ b/example.py
+@@ -1,5 +1,6 @@
+-def greet():
+-    print("Hello, world!")
++def greet_user(name):
++    print(f"Hello, {name}!")
+
+-def farewell():
+-    print("Goodbye!")
++def farewell_user(name):
++    print(f"Goodbye, {name}!")
+"""
+
+#keep the instrcution unchanged, becus the model was trained on this static instruction 
+instruction = "Generate a commit message based on the following Git diff:\n\n"
+
+task_input = instruction + git_diff
+
+# Tokenize the input
+inputs = tokenizer(
+    task_input,
+    max_length=512,  # Truncate if necessary
+    truncation=True,
+    padding="max_length",
+    return_tensors="pt"
+)
+
+# Generate commit message
+outputs = model.generate(
+    inputs["input_ids"],
+    max_length=50,
+    num_beams=5,       # Use beam search
+    temperature=0.9,   # Adds controlled randomness
+    top_p=0.9,         # Nucleus sampling
+    early_stopping=True
+)
+
+# Decode the generated commit message
+commit_message = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Print the result
+print("Generated Commit Message:")
+print(commit_message)
+```