XXXiong/ChatHLS-HLSFixer

TEXT GENERATIONConcurrent Unit Cost:1Model Size:14.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Apr 20, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

ChatHLS-HLSFixer by XXXiong is a specialized large language model fine-tuned from Qwen2.5-14B-Instruct for High-Level Synthesis (HLS) C/C++ error correction. It functions as the core analysis agent within the ChatHLS framework, designed to debug buggy HLS code by analyzing compiler error logs and code differences. This model excels at identifying erroneous code lines, explaining bug reasons, and proposing specific fixes for HLS-incompatible errors.

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ChatHLS-HLSFixer: Specialized HLS Debugging LLM

ChatHLS-HLSFixer is a highly specialized Large Language Model developed by XXXiong, fine-tuned from Qwen/Qwen2.5-14B-Instruct. Its primary purpose is to act as a core analysis agent within the ChatHLS framework, focusing on High-Level Synthesis (HLS) C/C++ error correction.

Key Capabilities

  • HLS Error Identification: Pinpoints erroneous code lines in C/C++ programs that are incompatible with HLS.
  • Root Cause Analysis: Explains the underlying reasons for HLS bugs by analyzing compiler error logs and comparing buggy code with expected patterns.
  • Automated Fix Proposals: Generates specific, actionable modification actions to resolve identified HLS errors.
  • Chain of Thought (CoT) Debugging: Employs a structured CoT strategy to guide the debugging process, addressing errors sequentially and validating hypotheses.
  • Structured Output: Provides bug analysis in a standardized JSON format, detailing erroneous lines, reasons, and proposed fixes.

Good For

  • Automated HLS Debugging: Ideal for developers and researchers working with High-Level Synthesis who need to quickly identify and fix HLS-incompatible errors in C/C++ code.
  • Integrating into HLS Toolchains: Can be integrated into larger HLS design automation and optimization frameworks, such as the ChatHLS project.
  • Educational Purposes: Useful for understanding common HLS pitfalls and debugging strategies through its detailed CoT output.