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Mercity/bhagavad_gita-embeddings

Bhagavad Gita Embedding DatasetThis repository contains a specialized embedding dataset of the ancient Indian epic, Bhagavad Gita, suitable for various NLP tasks, semantic search, and text retrieval purposes. Dataset relesased by Mercity AI! Dataset SourceThe original textual data has been sourced from the repository: VedaBase.io - Bhagavad Gita Library by ISKCON We extend our sincere gratitude to ISKCON and the maintainers of VedaBase.io for compiling and openly sharing valuable Sanskrit… See the full description on the dataset page: https://huggingface.co/datasets/Mercity/bhagavad_gita-embeddings.

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Bhagavad Gita Embedding Dataset This repository contains a specialized embedding dataset of the ancient Indian epic, Bhagavad Gita, suitable for various NLP tasks, semantic search, and text retrieval purposes.

Dataset relesased by Mercity AI!

Dataset Source The original textual data has been sourced from the repository: VedaBase.io - Bhagavad Gita Library by ISKCON

We extend our sincere gratitude to ISKCON and the maintainers of VedaBase.io for compiling and openly sharing valuable Sanskrit literature datasets.

Embedding Models Used The textual embeddings provided in this dataset have been generated using the following embedding models:

Type: Transformer-based sentence embedding model Usage: Particularly suited for semantic search, clustering, and information retrieval tasks.

Type: Transformer-based sentence embedding model Usage: Efficient and lightweight embeddings suitable for general semantic search and retrieval tasks.

Dataset Structure Each entry in the dataset contains:

  • —id: A unique identifier for each verse/excerpt.
  • —sanskrit_text: The original textual content in Sanskrit from Ramayana.
  • —translation: English translation of the Sanskrit text.
  • —minilm_embedding: Vector representation (384-dimensional embedding) generated using the sentence-transformers/all-MiniLM-L6-v2
  • —bge_embedding: Vector representation (1024-dimensional embedding) generated using the BAAI/bge-large-en-v1.5