README.md

metadata

language: en
license: mit
tags:
  - code-review
  - agent
  - text-generation
  - distilgpt2
widget:
  - text: |-
      Review this code:
      def get_user(id):
          return users[id]
    example_title: Missing null check
  - text: |-
      Improve this loop:
      for i in range(len(items)):
          process(items[i])
    example_title: Inefficient loop
  - text: |-
      Fix this average calculation:
      def avg(data):
          return sum(data)/len(data)
    example_title: Division by zero

Code Review Agent Model

This is a lightweight language model (based on distilgpt2) designed to generate helpful code review comments. It is a starting point for building an AI that reviews pull requests, suggests improvements, and catches common bugs.

Model Details

• Base model: distilgpt2 – a distilled version of GPT-2 with 82M parameters.
• Language: English
• Intended use: Generating code review comments, suggesting fixes, and answering questions about code.
• Limitations: The model has not been fine‑tuned on code‑review data; it may produce generic or off‑topic responses. Fine‑tuning on a dataset of real code reviews would greatly improve its utility.

How to Use

With transformers pipeline

from transformers import pipeline

pipe = pipeline("text-generation", model="your-username/code-review-agent")

code = "def get_user(id):\n    return users[id]  # missing null check"
prompt = f"Review this code:\n{code}\nComment:"
result = pipe(prompt, max_new_tokens=100, do_sample=True, temperature=0.7)
print(result[0]['generated_text'])