mcptester0606/Annoy-PyEdu-Rs

Annoy: This should be a paper Title

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Dataset

Dataset	Link
Annoy-PythonEdu-Rs	🤗

Please also check the raw data after our processing if you are interested: [mcptester0606/Annoy-PyEdu-Rs-Raw](https://huggingface.co/datasets/mcptester0606/Annoy-PyEdu-Rs-Raw).

Models

Base Model / Training	Annoy		Annoy++
	Stage 1	Stage 2	Stage 1	Stage 2
Qwen 2.5 7B Coder	🤗	🤗	🤗	🤗
LLaMA 3.1 8B	🤗	🤗	🤗	🤗
DeepSeek v2 Lite Coder	🤗	🤗	🤗	🤗

Introduction

While having full executable code theoretically allows us to generate reliable execution trajectories as responses, two challenges arise: 1) Obtaining a deterministic reverse function for input prediction is impractical; 2) Automatically constructed trajectories are constrained by pre-designed templates and lack the expressiveness and generalizability of free-form natural language reasoning. Thus, we adopt a fully LLM-based approach for synthesizing all the desired responses using DeepSeek-V2.5, as it has top-tier performance but extremely low cost compared to other advanced LLMs.

*Due to our collaborators' compliance requirements, we only release the PythonEdu-Rs subset (this page) of full dataset.