What are available pre-trained Embdding models | Open Source Embedding models | Embedding model repo

Описание: This video is part of Zero-to-Hero in NLP(Natural Language Processing),LLM(Large Language Model) and GenAI(GenerativeAI)

Embedding is the backbone of almost all NLP task like Semantic Search, Clustering, Recommendations, Anomaly detection, Question Answering, Classification and many more….

Embeddings play a pivotal role in natural language processing by converting words into numerical vectors to capture semantic relationships between words & sentences in the whole corpus, enabling machines to understand context and meaning of human language as close as possible like human.

Their importance lies in providing a numerical foundation for language understanding, enabling machines to navigate the complexities of human communication effectively. In essence, embeddings are the linchpin for the success of various language-based applications in the realms of NLP and LLM.

Essentially, in the development of your use case, there is no necessity to embark on the pre-training of a new embedding model. Instead, you can leverage the convenience of readily available embedding models. Depending on your budget constraints and the specific requirements of your use case, you have the flexibility to opt for a paid provider such as Google or OpenAI, or alternatively, choose from the array of available open-source options. This approach not only expedites the development process but also allows you to select a model that best suits your project's unique demands.

Let's dive in and unravel the magic of converting textual information into embedding.
Following topics are covered in this video:
🎯The significant breakthroughs in embedding technology throughout history
🎯 Different Embedding models
🎯 Embedding Models on SentenceTransformer model repository
🎯 Embedding models on HuggingFace

Happy Learning,
Pramod Singh
PGD - Data Science
Founder: datasciencechampion.in
About me :   / pramod-singh-4635962