Skywork SWE 32B GGUF

🚀 Skywork SWE 32B - A Community Model by Skywork

Part of the LM Studio Community models highlights program, which showcases new and remarkable models from the community. Join the discussion on Discord.

This model aims to provide high - performance solutions for software engineering tasks, leveraging advanced code - generation capabilities.

🚀 Quick Start

There is no specific quick - start guide provided in the original document.

✨ Features

• Quantization: Quantized by bartowski based on llama.cpp release b5697.
• Context Length: Supports a context length of 32k tokens.
• Benchmark Performance: Achieves 38.0% pass@1 accuracy on the SWE - bench Verified benchmark, outperforming previous open - source SoTA LLMs. With test - time scaling techniques, the accuracy can reach 47.0%.

📦 Installation

There is no installation guide provided in the original document.

💻 Usage Examples

There are no code examples provided in the original document.

📚 Documentation

Model Information

Model Description

Skywork - SWE - 32B is a code agent model developed by Skywork AI, specifically designed for software engineering (SWE) tasks.

🔧 Technical Details

• Context Length: Supports a context length of 32k tokens.
• Benchmark Performance: Skywork - SWE - 32B attains 38.0% pass@1 accuracy on the SWE - bench Verified benchmark, outperforming previous open - source SoTA [Qwen2.5 - Coder - 32B - based](https://huggingface.co/Qwen/Qwen2.5 - Coder - 32B) LLMs built on the [OpenHands](https://github.com/All - Hands - AI/OpenHands) agent framework. When incorporated with test - time scaling techniques, the performance further improves to 47.0% accuracy, surpassing the previous SoTA results for sub - 32B parameter models.

📄 License

The model is licensed under the apache - 2.0 license.

Special thanks

Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

Disclaimers

⚠️ Important Note

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