This index can be loaded from the Hugging Face Hub with txtai as shown below.
1from txtai import Embeddings
2
3# Load the index from the HF Hub
4embeddings = Embeddings()
5embeddings.load(provider="huggingface-hub", container="neuml/txtai-neuml-linkedin")
6
7# Search for posts discussing txtai
8embeddings.search("txtai")
NeuML LinkedIn Company Posts is an exploratory dataset to analyze the most engaging topics discussed on
NeuML's LinkedIn company page.
An embeddings index generated by txtai is a fully encapsulated index format. It doesn't require a database server or dependencies outside of the Python install.
Read more about this model and how it was built in
this article.
