> ## Documentation Index
> Fetch the complete documentation index at: https://docs.athina.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Import a HuggingFace Dataset

[Try it out on Google Colab →](https://colab.research.google.com/drive/1jxaHNTLvRhsie124ujxneA3izKvZNBuw?usp=sharing)

[Try Athina IDE →](https://demo.athina.ai/huggingface)

This guide demonstrates how to log a dataset from HuggingFace into Athina using Python. We'll walk through the process step-by-step, explaining each part of the code and its purpose.

## Prerequisites

Before you begin, make sure you have:

1. An Athina account and API key (you can sign up for free [here](https://app.athina.ai))
2. Python installed on your system
3. The necessary Python libraries: `datasets`, `athina-client`

## Step-by-Step Guide

### 0. Get your Athina API Key

You can get an Athina API key by signing up at [https://app.athina.ai](https://app.athina.ai)

### 1. Install Required Libraries

Install and import the required libraries to get started.

```python
pip install datasets athina-client
```

```python
import os
from athina_client import AthinaApiKey
from athina_client.datasets import Dataset
from datasets import load_dataset
```

Also, set your Athina API key:

```python
AthinaApiKey.set_key(os.getenv("ATHINA_API_KEY"))
```

### 2. Load the Dataset from HuggingFace

```python
HF_DATASET_ID = "openai/gsm8k"
SUBSET = "main"
SPLIT = "train"
LIMIT = 1000 # Number of rows to add - max. 1000

# Load a dataset from Hugging Face
hf_dataset = load_dataset(path=HF_DATASET_ID, data_dir=SUBSET, split=SPLIT)

# Define rows to add
rows = hf_dataset.to_list()[:1000]
```

*Currently, you can add a maximum of 1000 rows to a dataset in Athina.*

### 3. Log the Dataset to Athina

We'll use the `athina_client` library to log the dataset to Athina.

```python
# Create a dataset on Athina
athina_dataset = Dataset.create(name=f"{HF_DATASET_ID}-{SUBSET}-{SPLIT}", rows=rows)

# Print the dataset URL
print (f"View dataset on Athina: https://app.athina.ai/develop/{athina_dataset.id}")
```

***

[Athina](https://app.athina.ai) is a collaborative IDE that lets teams experiment, evaluate, and monitor AI applications in a spreadsheet-like UI.

### What Can You Do After Creating a Dataset?

* Run [dynamic prompts](/datasets/dynamic-columns/dynamic-columns-run-prompt) on every row, using other columns as variables.
* Transform the dataset by executing custom code.
* Create custom [evaluations](/evals) or run 50+ [preset evals](/evals/preset-evals) and view metrics in a powerful dashboard.
* Use [dynamic columns](/datasets/dynamic-columns/dynamic-columns) to classify text, retrieve data, extract entities, transform data, fetch from external APIs, and more.
* [Experiment](/datasets/run-experiment) with multiple combinations of prompts and models simultaneously.