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mm-tool/Annoy-PyEdu-Rs
Annoy-PyEdu-Rs is a machine learning model from mm-tool. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Updated Dec 12, 2025
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From the Hugging Face model README
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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/mm-tool/Annoy-PyEdu-Rs">🤗</a> </td> </tr> </table> Please also check the raw data after our processing if you are interested: [mm-tool/Annoy-PyEdu-Rs-Raw](https://huggingface.co/datasets/mm-tool/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/mm-tool/qwen2.5-7b-coder_spec_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/qwen2.5-7b-coder_spec">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/qwen2.5-7b-coder_spec_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/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/mm-tool/llama3.1-8b_spec_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/llama3.1-8b_spec">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/llama3.1-8b_spec_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/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/mm-tool/dsv2-lite-coder_spec_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/dsv2-lite-coder_spec">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/dsv2-lite-coder_spec_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/mm-tool/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 CC-BY-4.0.
License
The license for this dataset is The Stack v2 License.
License
The license for this dataset is Apache 2.0.