---
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.