| --- |
| dataset_info: |
| features: |
| - name: text |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 171220127 |
| num_examples: 50661 |
| download_size: 43815818 |
| dataset_size: 171220127 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
|
|
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - code |
| - python |
| - coding |
| - instruction-tuning |
| - chatml |
| - qlora |
| - atlas-coder |
| pretty_name: Atlas-Coder-50K-ChatML |
| size_categories: |
| - 10K<n<100K |
| task_categories: |
| - text-generation |
| --- |
| |
| # 📚 Atlas-Coder-50K-ChatML |
|
|
| A **50,000-sample execution-verified Python instruction dataset**, pre-formatted in **ChatML** for immediate supervised fine-tuning of coding language models. |
|
|
| This dataset accompanies **Atlas-Coder-2-0.5B** and represents the exact high-quality training subset used during instruction tuning. |
|
|
| --- |
|
|
| ## ✨ Highlights |
|
|
| - ✅ **50,000 curated Python instruction-response pairs** |
| - ✅ **Execution-verified** (compiled and tested before inclusion) |
| - ✅ **Pre-formatted in ChatML** |
| - ✅ **Ready for Hugging Face `Trainer` / `SFTTrainer`** |
| - ✅ **Decontaminated against HumanEval & MBPP** |
| - ✅ Optimized for **0.5B–3B parameter coding models** |
|
|
| --- |
|
|
| ## 📖 Dataset Description |
|
|
| Atlas-Coder-50K-ChatML is a carefully processed subset of the **bigcode/self-oss-instruct-sc2-exec-filter-50k** dataset. |
|
|
| Rather than increasing dataset size, the focus is on maximizing **signal quality**, enabling smaller language models to efficiently learn Python programming, algorithmic reasoning, and instruction following. |
|
|
| Each sample is already formatted in standard ChatML, eliminating the need for additional preprocessing before fine-tuning. |
|
|
| --- |
|
|
| ## 📂 Dataset Format |
|
|
| The dataset contains a single column: |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | `text` | string | Complete ChatML conversation | |
|
|
| Example: |
|
|
| ```text |
| <|im_start|>system |
| You are a helpful coding assistant. |
| <|im_end|> |
| <|im_start|>user |
| Write a function that returns the sum of all even numbers. |
| <|im_end|> |
| <|im_start|>assistant |
| def sum_even_numbers(lst): |
| return sum(x for x in lst if x % 2 == 0) |
| <|im_end|> |
| ``` |
|
|
| --- |
|
|
| ## 🚀 Loading the Dataset |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset( |
| "Siddh07ETH/Atlas-Coder-50K-ChatML", |
| split="train" |
| ) |
| |
| print(dataset[0]["text"]) |
| ``` |
|
|
| --- |
|
|
| ## 🛡️ Benchmark Integrity |
|
|
| Before training Atlas-Coder-2, the dataset was **decontaminated** against: |
|
|
| - HumanEval |
| - MBPP |
|
|
| using an **8-gram Jaccard similarity filter** with a **0.30 overlap threshold**. |
|
|
| Samples with excessive similarity to benchmark prompts were removed to preserve fair evaluation and prevent benchmark leakage. |
|
|
| --- |
|
|
| ## 🎯 Intended Use |
|
|
| This dataset is designed for: |
|
|
| - Instruction tuning |
| - Supervised fine-tuning (SFT) |
| - QLoRA training |
| - Small Language Models (SLMs) |
| - Python code generation |
| - Code completion |
| - Algorithmic reasoning |
|
|
| Recommended model sizes: |
|
|
| - 0.5B |
| - 1B |
| - 1.5B |
| - 3B |
|
|
| --- |
|
|
| ## ⚠️ Limitations |
|
|
| - Python-only dataset |
| - Does not include multilingual programming languages |
| - Optimized for functional code generation rather than long-form software engineering discussions |
|
|
| --- |
|
|
| ## 📄 License |
|
|
| This dataset is released under the **Apache-2.0** license and follows the licensing terms of the original **bigcode/self-oss-instruct-sc2-exec-filter-50k** dataset. |
|
|
