Autocoder : A new model for code generation tasks, achieving a higher test accuracy than GPT-4 Turbo.

Autocoder

AI code generation AI development assistant #Machine Learning #Text Generation #Code Generation #nlp-machine-learning #humaneval #llm #code-interpreter Standard Picks Open Source

Overview :

AutoCoder is a novel model specifically designed for code generation tasks. It outperforms GPT-4 Turbo (as of April 2024) and GPT-4-o on the HumanEval benchmark dataset. Unlike previous open-source models, AutoCoder introduces a new feature: it can automatically install required packages and attempt to run the code when the user wishes to execute it, ensuring it works without issues.

Target Users :

AutoCoder targets developers and programmers who need automatic code generation and validation. It helps them improve development efficiency and reduce time spent manually debugging code by providing high-accuracy code generation and automatic package installation.

Total Visits： 474.6M

Top Region： US(19.34%)

Website Views ： 59.9K

Use Cases

Developers use AutoCoder to automatically generate code, accelerating development speed.

Educational institutions leverage AutoCoder for programming education, helping students understand the code generation process.

Businesses utilize AutoCoder for code quality control, minimizing human errors.

Features

Achieves 90.9% accuracy on the HumanEval benchmark dataset, surpassing GPT-4 Turbo.

Automatically installs required packages and attempts to run the code when needed.

Provides a code interpreter to verify the correctness of the code.

Offers a web demo, including the code interpreter functionality.