candle_embed
A simple, CUDA or CPU powered, library for creating vector embeddings using Candle and models from Hugging Face (by ShelbyJenkins)
pg_vectorize
The simplest way to orchestrate vector search on Postgres (by tembo-io)
candle_embed | pg_vectorize | |
---|---|---|
2 | 5 | |
10 | 647 | |
- | 10.2% | |
4.7 | 9.2 | |
14 days ago | 3 days ago | |
Rust | Rust | |
MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
candle_embed
Posts with mentions or reviews of candle_embed.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-17.
- Show HN: CandleEmbed – A crate for generating text embeddings from HF models
-
Embeddings are a good starting point for the AI curious app developer
Fun timing!
I literally just published my first crate: candle_embed[1]
It uses Candle under the hood (the crate is more of a user friendly wrapper) and lets you use any model on HF like the new SoTA model from Snowflake[2].
[1] https://github.com/ShelbyJenkins/candle_embed
pg_vectorize
Posts with mentions or reviews of pg_vectorize.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-17.
-
Embeddings are a good starting point for the AI curious app developer
check out https://github.com/tembo-io/pg_vectorize - we're taking it a little bit beyond just the storage and index. The project uses pgvector for the indices and distance operators, but also adds a simpler API, hooks into pre-trained embedding models, and helps you keep embeddings updated as data changes/grows
-
Pg_vectorize: The simplest way to do vector search and RAG on Postgres
There is a RAG example here https://github.com/tembo-io/pg_vectorize?tab=readme-ov-file#...
You can provide your own prompts by adding them to the `vectorize.prompts` table. There's an API for this in the works. It is poorly documented at the moment.
- Pg_vectorize – The simplest way to orchestrate vector search on Postgres
What are some alternatives?
When comparing candle_embed and pg_vectorize you can also consider the following projects:
fastembed-rs - Library to generate vector embeddings. Rust implementation of Qdrant's FastEmbed.
pgvector - Open-source vector similarity search for Postgres