text-embeddings-inference

A blazing fast inference solution for text embeddings models (by huggingface)

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text-embeddings-inference reviews and mentions

Posts with mentions or reviews of text-embeddings-inference. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2026-03-11.
  • Cut token waste across your entire team with the MCP Optimizer
    2 projects | dev.to | 11 Mar 2026
    The operator defaults to BAAI/bge-small-en-v1.5 as the model and runs the HuggingFace Text Embeddings Inference server. You can increase the replica count via spec.replicas to match your team's throughput needs. One shared instance serves every vMCP in the namespace. For all available configuration options, see the Optimizer docs.
  • The Case Against PGVector
    8 projects | news.ycombinator.com | 3 Nov 2025
    > what does the rag for uploaded files do in discourse?

    You can upload files that will act as RAG files for an AI bot. The bot can also have access to forum content, plus the ability to run tools in our sandboxed JS environment, making it possible for Discourse to host AI bots.

    > also, when i run a discourse search does it really do both a regular keyword search and a vector search? how do you combine results?

    Yes, it does both. In the full page search it does keyword first, then vector asynchronously, which can be toggled by the user in the UI. It's auto toggled when keyword has zero results now. Results are combined using reciprocal rank fusion.

    In the quick header search we simply append vector search to keyword search results when keyword returns less than 4 results.

    > does all discourse instances have those features? for example, internals.rust-lang.org, do they use pgvector?

    Yes, all use PGvector. In our hosting all instances default to having the vector features enabled, we run embeddings using https://github.com/huggingface/text-embeddings-inference

  • Embedding Text Documents with Qwen3
    1 project | news.ycombinator.com | 23 Aug 2025
    Just migrated all embeddings to this same model a few weeks ago in my company, and it's a game changer. Having 32k context is a 64x increase when compared with our previous used model. Plus being natively multilingual and producing very standard 1024 long arrays made it a seamless transition even with millions of embeddings across thousands of databases.

    I do recommend using https://github.com/huggingface/text-embeddings-inference for fast inference.

  • Zero-Shot Text Classification on a low-end CPU-only machine?
    6 projects | news.ycombinator.com | 7 Oct 2024
    Hugging Face does maintain a package named Text Embedding Inference (TEI) with GPU/CPU-optimized container images. While I have only used this for hosting embedding models, it does appear to support Roberta architecture classifiers (specifically sentiment analysis).

    https://github.com/huggingface/text-embeddings-inference

    You can always run a zero shot pipeline in HF with a simple Flask/FastAPI application.

  • Semantic Search On GitHub (prototype)
    5 projects | dev.to | 26 Aug 2024
    We used an AI model from Sentence Transformers. If you want an easy way to get started, we suggest checking out the HuggingFace Text Embedding API service. It lets you run your own API and create embeddings tailored to your needs.
  • HuggingFace text-generation-inference is reverting to Apache 2.0 License
    2 projects | news.ycombinator.com | 8 Apr 2024
    Worth noting that this also impacts the great https://github.com/huggingface/text-embeddings-inference, which allows anyone to run state of the art embeddings with great performance.
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  • Fast inference for text models using Rust
    1 project | news.ycombinator.com | 14 Oct 2023
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