Witness the Code LLM Battle: OpenAI vs WizardCoder!

Table of Contents

1. Introduction
2. Comparing Open AI with Wizard Coder
3. Benchmark Results for Wizard Coder
   1. Performance compared to GPT 4 and GPT 3.5
   2. Comparison with other open-source models
4. Task 1: Translating Java Code to Python
   1. Prompt for the task
   2. Evaluation and results
   3. Pros and Cons
5. Task 2: Translating MySQL Query to PostgreSQL
   1. Prompt for the task
   2. Evaluation and results
   3. Pros and Cons
6. Task 3: Assisting with Python Coding using Pandas
   1. Prompt for the task
   2. Evaluation and results
   3. Pros and Cons
7. Comparison between Wizard Coder and GPT 3.5
   1. Performance similarities and differences
   2. Use cases for Wizard Coder
8. Conclusion
9. FAQ
   1. How does Wizard Coder perform compared to GPT 3.5?
   2. Can Wizard Coder handle more complex tasks?
   3. Is Wizard Coder a good replacement for commercial models?

Comparing Open AI with Wizard Coder

In this article, we will compare the performance of Open AI with Wizard Coder, an open-source model. We will evaluate both models by giving them rudimentary tasks such as translating code and acting as coding assistants. The goal is to see how well Wizard Coder performs compared to Open AI, considering its lighter model with only 13 billion parameters. We'll also examine the benchmark results for Wizard Coder and compare them to other popular models like GPT 4 and GPT 3.5.

Benchmark Results for Wizard Coder

When compared to GPT 4 and GPT 3.5, Wizard Coder performs at a similar level for coding-related tasks. In fact, it outperforms other open-source models like Plot Bard and the new open-source model, King Falcon 40b instruct. The benchmark results Show that Wizard Coder is a viable alternative to commercial models.

Performance compared to GPT 4 and GPT 3.5

Wizard Coder's performance closely matches that of GPT 3.5, making it a powerful language model for coding-related tasks. While GPT 4 may offer advanced features, Wizard Coder proves to be competitive and reliable.

Comparison with other open-source models

Compared to other popular open-source models, such as Plot Bard and King Falcon 40b instruct, Wizard Coder stands out as a superior choice. The benchmark results highlight its effectiveness and demonstrate its capabilities in handling various coding tasks.

Task 1: Translating Java Code to Python

To evaluate the performance of Wizard Coder in translating Java code to Python, we provide a prompt and assess its output. The prompt instructs the model to translate the given Java code into its Python equivalent.

Prompt for the task

The prompt Prompts Wizard Coder to translate Java code to Python by providing the necessary Context. The Java code will be injected into the prompt, allowing the model to understand the task at HAND.

Evaluation and results

Wizard Coder successfully translates the provided Java code into Python. The output demonstrates its ability to accurately convert the program, showcasing a Python code snippet that determines whether a given input is a prime number. Overall, Wizard Coder performs exceptionally well in this task.

Pros:

• Accurate translation from Java to Python
• Efficient conversion of code

Cons:

• None identified

Task 2: Translating MySQL Query to PostgreSQL

In this task, we assess Wizard Coder's ability to convert a MySQL query into a PostgreSQL query. The prompt specifies the conversion requirement, and the model should provide the Relevant PostgreSQL query as the output.

Prompt for the task

The prompt instructs Wizard Coder to translate a MySQL query to a PostgreSQL query by considering the provided instruction below. The MySQL query is given as input, and the model should produce the equivalent PostgreSQL query.

Evaluation and results

Unfortunately, Wizard Coder fails to deliver an accurate conversion from MySQL to PostgreSQL. The provided output contains a PostgreSQL query with a function called "date format," which does not exist in PostgreSQL. This discrepancy highlights the model's limitation in handling certain MySQL-specific functions.

Pros:

• None identified

Cons:

• Inaccurate conversion from MySQL to PostgreSQL
• Limited support for specific MySQL functions in PostgreSQL

Task 3: Assisting with Python Coding using Pandas

For the third task, we examine Wizard Coder's capabilities as a coding assistant. The prompt requires the model to assist in writing a Python program using Pandas. The specific task is to sort a Pandas DataFrame using two keys, one in ascending order and the other in descending order.

Prompt for the task

The prompt provides the necessary context, instructing Wizard Coder to assist in sorting a Pandas DataFrame using two keys. It specifies the requirement for one key to be sorted in ascending order and the other in descending order.

Evaluation and results

The output from Wizard Coder showcases its effectiveness as a coding assistant. It accurately generates Python code that demonstrates how to sort a Pandas DataFrame using the specified keys, fulfilling the prompt requirements. The model's response is comparable to the output of Chat GPT, demonstrating its competence in assisting with coding tasks.

Pros:

• Accurate assistance in writing Python code
• Clear and concise explanation of the sorting process

Cons:

• None identified

Comparison between Wizard Coder and GPT 3.5

When comparing Wizard Coder with GPT 3.5, several similarities and differences become evident. In terms of performance, both models perform exceptionally well in handling coding-related tasks. While GPT 3.5 may offer additional features, Wizard Coder proves to be a valuable alternative, especially considering its lighter model size of 13 billion parameters.

Wizard Coder, being an open-source model, offers advantages such as transparency, community support, and the ability to fine-tune the model according to specific requirements. It performs closely to GPT 3.5, providing a robust solution for coding-related tasks.

Conclusion

In conclusion, Wizard Coder showcases its competence as an open-source model for handling coding-related tasks. Its performance is comparable to GPT 3.5, making it an effective choice for developers and coding enthusiasts. While it may not replace commercial models entirely, Wizard Coder's ability to handle tasks with only 13 billion parameters is impressive. It serves as a powerful coding assistant and translation tool.

FAQ

Q: How does Wizard Coder perform compared to GPT 3.5?

A: Wizard Coder performs closely to GPT 3.5, making it a reliable alternative for coding-related tasks. Its performance is comparable, showcasing its competence as an open-source model.

Q: Can Wizard Coder handle more complex tasks?

A: While Wizard Coder excels at rudimentary coding tasks, its performance in handling more complex tasks may vary. Its limited parameter size of 13 billion parameters may pose challenges for certain intricate scenarios.

Q: Is Wizard Coder a good replacement for commercial models?

A: Wizard Coder provides a viable alternative to commercial models, considering its performance and open-source nature. However, its suitability may depend on the specific requirements and complexity of the tasks at hand.