From 79d1992de03eccda4dbfb2065c41bfe39e269312 Mon Sep 17 00:00:00 2001 From: Tim Elfrink Date: Wed, 17 Sep 2025 07:50:38 +0200 Subject: [PATCH] Fix: MDX compilation error in CompactifAI documentation - Replace (<5%) with (under 5%) in two locations to fix JSX parsing - Resolves webpack build failure in Docusaurus documentation - Maintains same meaning while avoiding MDX syntax conflicts Fixes #14624 --- docs/my-website/docs/providers/compactifai.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/my-website/docs/providers/compactifai.md b/docs/my-website/docs/providers/compactifai.md index 0e6e8f4ed3..1aa8146307 100644 --- a/docs/my-website/docs/providers/compactifai.md +++ b/docs/my-website/docs/providers/compactifai.md @@ -4,7 +4,7 @@ import TabItem from '@theme/TabItem'; # CompactifAI https://docs.compactif.ai/ -CompactifAI offers highly compressed versions of leading language models, delivering up to **70% lower inference costs**, **4x throughput gains**, and **low-latency inference** with minimal quality loss (<5%). CompactifAI's OpenAI-compatible API makes integration straightforward, enabling developers to build ultra-efficient, scalable AI applications with superior concurrency and resource efficiency. +CompactifAI offers highly compressed versions of leading language models, delivering up to **70% lower inference costs**, **4x throughput gains**, and **low-latency inference** with minimal quality loss (under 5%). CompactifAI's OpenAI-compatible API makes integration straightforward, enabling developers to build ultra-efficient, scalable AI applications with superior concurrency and resource efficiency. | Property | Details | |-------|-------| @@ -192,7 +192,7 @@ Common model formats: ## Benefits - **Cost Efficient**: Up to 70% lower inference costs compared to standard models -- **High Performance**: 4x throughput gains with minimal quality loss (<5%) +- **High Performance**: 4x throughput gains with minimal quality loss (under 5%) - **Low Latency**: Optimized for fast response times - **Drop-in Replacement**: Full OpenAI API compatibility - **Scalable**: Superior concurrency and resource efficiency