From 3ef4acb0729013719748bde4c8eb5d0f58e7d584 Mon Sep 17 00:00:00 2001 From: Xiao Yang <xiaoyangfb@meta.com> Date: Sun, 31 Mar 2024 02:38:39 +0000 Subject: [PATCH] Update 5th point under Getting Started. --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3b6ed75..1ca69c8 100644 --- a/README.md +++ b/README.md @@ -47,7 +47,7 @@ Please refer to [local_evaluation.py](local_evaluation.py) for more details on h 2. **Fork** this starter kit repository. You can use [this link](https://gitlab.aicrowd.com/aicrowd/challenges/meta-comprehensive-rag-benchmark-kdd-cup-2024/meta-comphrehensive-rag-benchmark-starter-kit/-/forks/new) to create a fork. 3. **Clone** your forked repo and start developing your model. 4. **Develop** your model(s) following the template in [how to write your own model](#how-to-write-your-own-model) section. -5. [**Submit**](#-how-to-make-a-submission) your trained models to [AIcrowd Gitlab](https://gitlab.aicrowd.com) for evaluation [(full instructions below)](#-how-to-make-a-submission). The automated evaluation setup will evaluate the submissions on the private datasets and report the metrics on the leaderboard of the competition. +5. [**Submit**](#-how-to-make-a-submission) your trained models to [AIcrowd Gitlab](https://gitlab.aicrowd.com) for evaluation [(full instructions below)](#-how-to-make-a-submission). The automated evaluation will evaluate the submissions on the public test set and report the metrics on the leaderboard of the competition. # âœï¸ How to write your own model? -- GitLab