From 88b595f3ec82e209ba38cde64ad8b0cbd888aa43 Mon Sep 17 00:00:00 2001 From: NirantK Date: Thu, 24 Aug 2023 13:16:46 +0530 Subject: [PATCH] * chore: update project description in pyproject.toml * docs: update project description in README.md and docs/index.md --- README.md | 4 +++- docs/index.md | 4 +++- pyproject.toml | 2 +- 3 files changed, 7 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index b21d74c2..011b36ab 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,8 @@ # ⚡️ What is FastEmbed? -FastEmbed is an easy to use -- lightweight, fast, Python library built for retrieval augmented generation. The default embedding supports "query" and "passage" prefixes for the input text. +FastEmbed is an easy to use -- lightweight, fast, Python library built for retrieval embedding generation. + +The default embedding supports "query" and "passage" prefixes for the input text. The default model is Flag Embedding, which is top of the [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard. 1. Light - Quantized model weights diff --git a/docs/index.md b/docs/index.md index 2aa145bc..70594679 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,6 +1,8 @@ # ⚡️ What is FastEmbed? -FastEmbed is an easy to use -- lightweight, fast, Python library built for retrieval augmented generation. The default embedding supports "query" and "passage" prefixes for the input text. +FastEmbed is an easy to use -- lightweight, fast, Python library built for retrieval embedding generation. The default embedding supports "query" and "passage" prefixes for the input text. + +The default embedding supports "query" and "passage" prefixes for the input text. The default model is Flag Embedding, which is top of the [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard. ## 🚀 Installation diff --git a/pyproject.toml b/pyproject.toml index a5255f98..b7b081ba 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,7 +1,7 @@ [tool.poetry] name = "fastembed" version = "0.0.4" -description = "Fast, State of the Art Quantized Embedding Models" +description = "Fast, light, accurate library built for retrieval embedding generation" authors = ["NirantK "] license = "Apache License" readme = "README.md"