| --- |
| license: apache-2.0 |
| task_categories: |
| - text-classification |
| tags: |
| - code |
| - language-identification |
| - qwen |
| pretty_name: Qwen Code Language-ID SFT Dataset |
| --- |
| |
| # Accuknoxtechnologies/CodeLanguage |
|
|
| SFT dataset for fine-tuning a Qwen-based guard that detects which programming languages appear in a user prompt. Each row pairs a natural-language + code prompt with a JSON `target` enumerating the detected languages. |
|
|
| This release combines the previously-separate train + test CSVs into a single `train` split (source files: `code_langid.csv`, `test_dataset_langid.csv`). |
|
|
| ## Schema |
|
|
| | column | description | |
| |---|---| |
| | `prompt` | user message, possibly containing one or more code snippets | |
| | `target` | JSON: `{"is_valid": bool, "category": {"<Lang>": true, ...}}` | |
| | `kind` | one of `single`, `multi`, `benign` | |
|
|
| ## Total Records |
|
|
| | rows | single | multi | benign | invalid (`is_valid=false`) | |
| |---:|---:|---:|---:|---:| |
| | 10500 | 7349 | 2101 | 1050 | 1050 | |
|
|
| ## Supported Labels |
|
|
| 25 programming languages: |
|
|
| `AWK`, `Bash`, `Batch`, `C`, `C#`, `C++`, `Dockerfile`, `Go`, `Java`, `JavaScript`, `Kotlin`, `Lua`, `Makefile`, `Perl`, `PowerShell`, `Python`, `R`, `Ruby`, `Rust`, `SQL`, `Scala`, `Swift`, `Terraform`, `YAML`, `jq` |
|
|
| | label | rows containing label | |
| |---|---:| |
| | `Go` | 508 | |
| | `PowerShell` | 505 | |
| | `Lua` | 504 | |
| | `Terraform` | 502 | |
| | `Rust` | 498 | |
| | `AWK` | 496 | |
| | `Kotlin` | 496 | |
| | `JavaScript` | 495 | |
| | `Batch` | 495 | |
| | `C` | 492 | |
| | `C++` | 491 | |
| | `Scala` | 486 | |
| | `Ruby` | 486 | |
| | `jq` | 480 | |
| | `R` | 479 | |
| | `Dockerfile` | 475 | |
| | `Swift` | 472 | |
| | `C#` | 469 | |
| | `Makefile` | 467 | |
| | `Bash` | 466 | |
| | `Perl` | 466 | |
| | `SQL` | 465 | |
| | `Python` | 462 | |
| | `Java` | 460 | |
| | `YAML` | 448 | |
|
|
| ## Token-wise Bucket Split |
|
|
| Tokenized with `Qwen/Qwen2.5-0.5B` (matches the training tokenizer). |
|
|
| | 0-128 | 129-256 | 257-512 | 513-1024 | 1025-2048 | 2049+ | min | mean | p50 | p95 | max | |
| |---|---|---|---|---|---|---|---|---|---|---| |
| | 1529 | 1725 | 2398 | 2759 | 2060 | 29 | 23 | 581.8 | 449 | 1361 | 3035 | |
|
|
| ## Languages (natural language of the prompts) |
|
|
| _Per-prompt natural-language detection (English/Korean/etc.) is not computed in this card revision. Prompts are predominantly English by construction (see `build_dataset.py`)._ |
|
|
| ## Reproduction |
|
|
| Generated by `gpu-vm-training-langid/build_dataset.py` and pushed by `gpu-vm-training-langid/hf_dataset_push/push_dataset.py`. |
|
|
