Annoy-PyEdu-Rs

Annoy: This should be a paper Title

<p align="left"> 📑 <a href="https://huggingface.co/papers/xxxx.xxxxx" target="_blank">Paper</a> &nbsp&nbsp | &nbsp&nbsp 🌐 <a href="https://specx.github.io/" target="_blank">Project Page</a> &nbsp&nbsp | &nbsp&nbsp 💾 <a href="https://huggingface.co/collections/toolathlon-eval-02/specx-67a978e28fd926b56a4f55a2" target="_blank">Released Resources</a> &nbsp&nbsp | &nbsp&nbsp 📦 <a href="https://github.com/tooalthon-user-11-sketch/Annoy" target="_blank">Repo</a>

This is the resource page of the our resources collection on Huggingface, we highlight your currect position with a blue block.

Dataset

<table> <tr> <th>Dataset</th> <th>Link</th> </tr> <tr> <td>Annoy-PythonEdu-Rs</td> <td style="background-color: #e6f3ff; text-align: center; vertical-align: middle;"> <a href="https://huggingface.co/datasets/toolathlon-eval-02/Annoy-PyEdu-Rs">🤗</a> </td> </tr> </table> Please also check the raw data after our processing if you are interested: [toolathlon-eval-02/Annoy-PyEdu-Rs-Raw](https://huggingface.co/datasets/toolathlon-eval-02/Annoy-PyEdu-Rs-Raw).

Models

<table> <tr> <th rowspan="2">Base Model / Training</th> <th colspan="2">Annoy</th> <th colspan="2">Annoy++</th> </tr> <tr> <th>Stage 1</th> <th>Stage 2</th> <th>Stage 1</th> <th>Stage 2</th> </tr> <tr> <td>Qwen 2.5 7B Coder</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/qwen2.5-7b-coder_spec_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/qwen2.5-7b-coder_spec">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/qwen2.5-7b-coder_spec_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/qwen2.5-7b-coder_spec_pp">🤗</a></td> </tr> <tr> <td>LLaMA 3.1 8B</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/llama3.1-8b_spec_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/llama3.1-8b_spec">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/llama3.1-8b_spec_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/llama3.1-8b_spec_pp">🤗</a></td> </tr> <tr> <td>DeepSeek v2 Lite Coder</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/dsv2-lite-coder_spec_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/dsv2-lite-coder_spec">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/dsv2-lite-coder_spec_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/toolathlon-eval-02/dsv2-lite-coder_spec_pp">🤗</a></td> </tr> </table>

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.

License

The license for this dataset is odc-by.