| --- |
| license: apache-2.0 |
| task_categories: |
| - text-generation |
| - sentence-similarity |
| language: |
| - en |
| tags: |
| - code |
| pretty_name: NPset-Python |
| size_categories: |
| - 1M<n<10M |
| --- |
|  |
|
|
| # NPset |
|
|
| A normalized semi-sythetic Python dataset for training small language models on code logic without the overhead of raw code syntax. |
|
|
|  |
|
|
| ## Why |
|
|
| Small language models trained on natural language corpora develop latent representations of logical constructs -- iteration, conditionals, data flow, function composition -- yet struggle to apply this reasoning to source code, where syntactic overhead (delimiters, indentation conventions, language-specific idioms) occupies a disproportionate share of the token budget, requires a vocabulary of code-specific tokens rarely encountered during pretraining, and introduces a surface-form distribution shift relative to the model's prior knowledge. NPset addresses this by normalizing Python source through an AST-based converter that strips syntactic noise while preserving the full logical structure of each program, producing a pseudocode representation composed entirely of natural language tokens that aligns more directly with the semantic representations already present in small models, allowing them to reason about what code *does* rather than expending capacity learning what it *looks like*. |
|
|
| ## Format |
|
|
| Parquet, shuffled. Each row: |
|
|
| | Field | Type | Description | |
| |---|---|---| |
| | `code` | string | Normalized pseudocode | |
| | `original_code` | string | Original Python source | |
| | `original_language` | string | Always `Python` | |
| | `source` | string | Origin dataset identifier | |
|
|
| ## Sources |
|
|
| | Source | Dataset | Rows | |
| |---|---|---:| |
| | `nomic_cornstack_python_v1` | nomic-ai/cornstack-python-v1 | 3,498,845 | |
| | `zaydzuhri_stack_edu_python` | zaydzuhri/stack-edu-python (`license_type=no_license`) | 3,543,752 | |
| | `jtatman_500k` | jtatman/python-code-dataset-500k | 32,590 | |
| | `iamtarun_python_18k_alpaca` | iamtarun/python_code_instructions_18k_alpaca | 17,496 | |
| | `flytech_python_25k` | flytech/python-codes-25k | 42,968 | |
| | `dbands_pythonMath` | dbands/pythonMath | 5,726 | |
| | `greatdarklord_python_dataset` | greatdarklord/python_dataset | 18,452 | |
| | | **Total** | **7,159,829** | |
