Update README.md

README.md

@@ -8,6 +8,8 @@ datasets:
 - openbmb/EVisRAG-Train
 ---
 
+This is a temporary repo forked from openbmb/evisrag-7b.
+
 # VisRAG 2.0: Evidence-Guided Multi-Image Reasoning in Visual Retrieval-Augmented Generation
 [![Github](https://img.shields.io/badge/VisRAG-000000?style=for-the-badge&logo=github&logoColor=000&logoColor=white)](https://github.com/OpenBMB/VisRAG)
 [![arXiv](https://img.shields.io/badge/arXiv-2510.09733-ff0000.svg?style=for-the-badge)](https://arxiv.org/abs/2510.09733)
@@ -37,7 +39,7 @@ datasets:
 
 # ✨ EVisRAG Pipeline
 
-**EVisRAG** is an end-to-end framework which equips VLMs with precise visual perception during reasoning in multi-image scenarios. We trained and realeased VLRMs with EVisRAG built on [Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct), and [Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct).
+**EVisRAG** is an end-to-end framework which equips VLMs with precise visual perception during reasoning in multi-image scenarios. We trained and released VLRMs with EVisRAG built on [Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct), and [Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct).
 
 # ⚙️ Setup
 ```bash
@@ -112,7 +114,7 @@ If none of the images contain sufficient information to answer the question, res
 Formatting Requirements:
 Use the exact tags <observe>, <evidence>, <think>, and <answer> for structured output.
 It is possible that none, one, or several images contain relevant evidence.
-If you find no evidence or few evidences, and insufficient to help you answer the question, follow the instruction above for insufficient information.
+If you find no evidence or little evidence, and insufficient to help you answer the question, follow the instructions above for insufficient information.
 
 Question and images are provided below. Please follow the steps as instructed.
 Question: {query}