Datasets:
File size: 3,359 Bytes
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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.
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