Update README.md

README.md

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+# Recipe Short - Dense and Sparse Embeddings Dataset
+
+This dataset is based on the [rk404/recipe_short](https://huggingface.co/datasets/rk404/recipe_short) dataset. It includes dense and sparse embeddings for each recipe, generated using two specific models: 
+
+1. **Dense Embeddings**: Created using the `sentence-transformers/all-MiniLM-L6-v2` model with `fastembed` library.
+2. **Sparse Embeddings**: Generated using the `Qdrant/bm25-all-minilm-l6-v2-attentions` model with `fastembed` library.
+
+The embeddings were computed using GPU resources on Kaggle for efficient processing. This dataset is intended for tasks related to text similarity, search, and semantic information retrieval within recipe-related content.
+
+
+### Sparse Embedding Model Reference
+
+Sparse vector embedding model focuses on capturing the most important tokens from the text. It provides attention-based scores to highlight key terms, which can be beneficial for keyword-based search and sparse retrieval tasks.
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+You can find more about sparse embedding [here](https://qdrant.tech/articles/bm42/#:~:text=Despite%20all%20of%20its%20advantages,%20BM42) and [here](https://github.com/qdrant/bm42_eval/)
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+### Generation Code
+