SkyCode-AI-CodeX-GPT3: A Comprehensive Project Overview
SkyCode, developed by QiDian ZhiYuan, is an open-source, multilingual programming model inspired by the GPT-3 architecture and trained with a vast dataset of code. The model is proficient in a broad spectrum of popular programming languages, such as Java, JavaScript, C, C++, Python, Go, and shell scripting, and it has enhanced capabilities for understanding Chinese annotations. SkyCode is designed to assist with code completion and problem-solving tasks, allowing developers to focus more on addressing larger, complex problems.
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Project Highlights
1. Versatile Language Coverage
SkyCode stands out with its ability to generate code in a diverse array of programming languages, not only limited to widely used languages like JavaScript, Python, and Java, but also extending to languages such as PHP, Go, and Swift, among others. This extensive language support ensures developers from different language backgrounds can leverage SkyCode’s robust code-generation capabilities.
2. Optimized for Chinese Annotations
A unique advantage of SkyCode is its optimization for Chinese annotations within the code. Historically, the pretraining of models like GPT-3 has been predominantly English-focused. Here, QiDian ZhiYuan's in-depth experience with Chinese models is pivotal, having innovatively adapted a unique Chinese encoding method, enhancing the model's ability to comprehend Chinese annotations with remarkable precision.
3. Exceptional Problem-Solving Abilities
SkyCode demonstrates superior problem-solving abilities, particularly evident when evaluated against the HumanEval dataset, a benchmark for assessing code generation models. SkyCode, with a parameter size of 2.6 billion, outperforms several open-source models, including the GPT-Neo 1.3B and GPT-Neo 2.7B, and even surpasses the GPT-J 6B model. A noteworthy metric, pass@100, sees SkyCode delivering a substantial 8.23% higher success rate compared to GPT-J, showcasing its remarkable upper limit in problem-solving proficiency.
| Model | pass@1 | pass@10 | pass@100 |
|---|---|---|---|
| GPT-Neo 1.3B | 4.79% | 7.47% | 16.30% |
| GPT-Neo 2.7B | 6.41% | 11.27% | 21.37% |
| GPT-J 6B | 11.62% | 15.74% | 27.74% |
| SKY_code(2.6B) | 12.84% | 21.07% | 35.97% |
QiDian News
- December 15, 2022: Release event of Kunlun Tiangong AIGC. Event Details
Model Usage and Dependencies
SkyCode is recommended for use with the transformers library version 4.18.0 or higher. Below is a sample code to illustrate how to implement the SkyCode model using Python:
# -*- coding: utf-8 -*-
from transformers import GPT2LMHeadModel
from transformers import AutoTokenizer
from transformers import TextGenerationPipeline
model = GPT2LMHeadModel.from_pretrained("SkyWork/SkyCode")
tokenizer = AutoTokenizer.from_pretrained("SkyWork/SkyCode", trust_remote_code=True)
text_generator = TextGenerationPipeline(model, tokenizer, device=0)
input_str = "if __name__"
max_new_tokens = 40
print(text_generator(input_str, max_new_tokens=max_new_tokens, do_sample=True))
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Licensing
SkyCode is distributed under the MIT License, allowing for free use and distribution.
Joining the Developer Community
Interested developers can join the SkyCode developer community by scanning the WeChat QR code to connect with fellow enthusiasts and contribute to the project's growth.
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