| --- |
| license: other |
| task_categories: |
| - text-generation |
| language: |
| - en |
| tags: |
| - code |
| - code-optimization |
| - cpp |
| - sft |
| - grpo |
| configs: |
| - config_name: sft |
| data_files: |
| - split: train |
| path: sft/train.jsonl |
| - config_name: grpo |
| data_files: |
| - split: train |
| path: grpo/train.jsonl |
| - config_name: evaluation |
| data_files: |
| - split: validation |
| path: eval/validation.jsonl |
| --- |
| |
| # GLM-4.7-Flash PIE C++ Post-Training Data |
|
|
| The exact prepared dataset used for the GLM-4.7-Flash C++ performance |
| post-training runs. |
|
|
| ## Splits |
|
|
| | File | Rows | Purpose | |
| | --- | ---: | --- | |
| | `sft/train.jsonl` | 7,864 | Supervised fine-tuning | |
| | `grpo/train.jsonl` | 7,887 | GRPO prompt and reward evaluation | |
| | `eval/validation.jsonl` | 1,259 | Full held-out evaluation | |
| | `eval/validation_mini126.jsonl` | 126 | Fast evaluation | |
| | `eval/validation_mini4.jsonl` | 4 | Smoke evaluation | |
| | `tasks.tar.gz` | 9,146 task JSONs | Reward scoring and evaluation harness inputs | |
|
|
| Each row carries a stable task ID, problem ID, split, prompt, label, and task |
| metadata. SFT rows additionally contain the user and assistant messages used by |
| the trainer. The task archive contains every `tasks/...` path referenced by the |
| training and evaluation rows. The canonical repository downloader verifies and |
| extracts it into `data/tasks`. |
|
|
| ## Preparation |
|
|
| The source tasks were filtered by compiling and executing the oracle answer in |
| the C++ sandbox. Training rows were retained when the response format was valid, |
| all tests passed, and the reward result was `correct`. |
|
|
| The source preparation run scored 8,350 training tasks, retained 7,887, and |
| rejected 463. The complete preparation receipt is in `manifest.json`. |
|
|
| ## Provenance |
|
|
| This is a prepared derivative of the |
| [PIE C++ performance dataset](https://github.com/madaan/pie-perf), which is |
| based on IBM Project CodeNet. Use and redistribution are subject to the |
| applicable upstream dataset terms. |
|
|
| Training code: |
| [TokenBender/browser-is-all-you-need](https://github.com/tokenbender/browser-is-all-you-need/tree/client/glm47-h100-posttraining) |
|
|
