Update README.md

README.md

@@ -62,3 +62,48 @@ license: apache-2.0
 task_categories:
 - translation
 ---
+
+
+## AfriMMD - African Multilingual Multimodal Dataset (POC)
+AfriMMD is a multilingual dataset created to enhance linguistic diversity in AI, 
+focusing on African languages. This is a proof-of-concept experiment on the use 
+of multimodal datasets to represent African languages in AI. The dataset contains 
+translations of the captions in the widely-used Flickr8k dataset into 20 African 
+languages. The goal is to address the underrepresentation of African languages 
+in AI and foster more inclusive AI technologies. The image-text pairs have been 
+carefully translated into multiple African languages, providing an avenue 
+for advanced and inclusive AI development, particularly in multimodal tasks that 
+involve both text and images.
+
+Images associated with the dataset can manually be downloaded from [Github](https://github.com/jbrownlee/Datasets/releases/tag/Flickr8k)
+or [Kaggle](https://www.kaggle.com/datasets/adityajn105/flickr8k?select=Images)
+
+## Supported Languages
+Amharic (amh), Bemba (bem), Chokwe (cjk), Rek (dik), Dyula (dyu), Ewe (ewe), 
+Fulfulde (fuv), Hausa (hau), Igbo (ibo), Kikuyu (kik), Kabyle (kab), 
+Kamba (kam), Kikongo (kon), Kimbundu (kmb), LubaKasai (lua), Ganda (lug),
+Lingala (lin), Kinyarwanda (kin), Yoruba (yor)
+
+
+## Load Dataset
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('AfriMM/AfriMMD')
+```
+
+## Applications
+- Multilingual multimodal tasks (eg: image captioning in African languages, pre-trained vision-language models, etc.)
+- Translation and language learning for supported African languages.
+- Research on cross-cultural understanding and representation in AI.
+
+
+## Citation
+```bibtex
+@dataset{afrimm2024,
+  author       = {AfriMM - ML Collective},
+  title        = {AfriMMD: Multimodal Dataset for African Languages},
+  year         = 2024,
+  url          = {https://huggingface.co/datasets/AfriMM/AfriMMD}
+}
+```