| --- |
| language: |
| - en |
| license: other |
| task_categories: |
| - text-generation |
| tags: |
| - cpp |
| - c |
| - code |
| - qwen3.5 |
| - conversation |
| - instruction-tuning |
| size_categories: |
| - 10K |
| --- |
| |
| # C / C++ Code Corpus |
|
|
| ## Description |
|
|
| Teaches domain-specific instruction following and code generation for this expert. |
|
|
| ## Source |
|
|
| - shareAI/CodeChat |
| - Mxode/StackOverflow-QA-C-Language-40k |
| - dumb-dev/cpp-10k |
| - AmareshHebbar/leetcode-codegen-cpp |
|
|
| Formatted for the MoE-orchestrator project |
| (https://github.com/michaelowusuntim6/MoE-orchestrator). Expert target: |
| `code_cpp`. |
|
|
| ## Format |
|
|
| Each record is a JSON object with a `messages` field formatted for Qwen3.5's |
| native chat template: |
|
|
| ```json |
| {"messages": [ |
| {"role": "system", "content": "..."}, |
| {"role": "user", "content": "..."}, |
| {"role": "assistant", "content": "..."} |
| ]} |
| ``` |
|
|
| The records are consumed via `tokenizer.apply_chat_template()`. Special tokens |
| (`<|im_start|>`, `<|im_end|>`) are added by the template, never embedded in |
| content. |
|
|
| ## Splits |
|
|
| - `train`: 33,419 records |
| - `val`: 712 records |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("michaelowusuntim6/cpp-qwen35", split="train") |
| print(ds[0]["messages"]) |
| ``` |
|
|
| ## License |
|
|
| mixed. Upstream sources keep their own licences - see the source list |
| above and `docs/DATASET_SOURCES.md` in the MoE-orchestrator repository for |
| per-source detail. |
|
|
