Update README.md

README.md

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+---
+language:
+- en
+license: cc-by-4.0
+pretty_name: Free Music Archive (FMA) Dataset
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- audio-classification
+task_ids:
+- multi-class-classification
+---
+
+# Free Music Archive (FMA) Dataset
+
+## Overview
+
+This repository contains the Free Music Archive (FMA) dataset, curated and made available on Hugging Face by [dragunflie-420](https://huggingface.co/dragunflie-420). The FMA dataset is a large-scale, open-source dataset of music tracks, designed for music information retrieval and machine learning tasks.
+
+## Dataset Description
+
+The Free Music Archive (FMA) is an open and easily accessible dataset consisting of full-length audio tracks with associated metadata. This particular version focuses on the "small" subset of the FMA, which includes:
+
+- 8,000 tracks of 30 seconds each
+- 8 balanced genres (Electronic, Experimental, Folk, Hip-Hop, Instrumental, International, Pop, Rock)
+- Audio files in 128k MP3 format
+- Comprehensive metadata for each track
+
+## Contents
+
+This dataset provides:
+
+1. Audio files: 30-second MP3 clips of music tracks
+2. Metadata: Information about each track, including:
+   - Track ID
+   - Title
+   - Artist
+   - Genre
+   - Additional features (e.g., acoustic features, music analysis data)
+
+## Data Files
+
+To use this dataset, you need to manually download and place the following files in the repository:
+
+1. `fma_small.zip`: Contains the audio files
+2. `fma_metadata.zip`: Contains the metadata for the tracks
+
+After downloading, extract these files and ensure the following directory structure:
+
+```
+fma_dataset/
+├── fma_small/
+│   ├── 000/
+│   ├── 001/
+│   └── ...
+└── fma_metadata/
+    ├── tracks.csv
+    ├── genres.csv
+    └── features.csv
+```
+
+## Usage
+
+To use this dataset in your Hugging Face projects:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("dragunflie-420/fma")
+
+# Access the first example
+first_example = dataset['train'][0]
+print(first_example['title'], first_example['artist'], first_example['genre'])
+
+# Play the audio (if in a notebook environment)
+from IPython.display import Audio
+Audio(first_example['audio']['array'], rate=first_example['audio']['sampling_rate'])
+```
+
+[... rest of the README content remains the same ...]
+
+
+
+
+
 ---
 language:
 - en