update data

README.md

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 ---
-license: apache-2.0
+language:
+- "en"
+
+pretty_name: "rare disease corpus"
+
+tags:
+- "rare disease corpus"
+- "rare-disease corpus"
+- "rare-disease database"
+
+license: "apache-2.0"
 ---
+
+# Dataset Card for ReCOP
+
+## What's for?
+
+The data for ReCOP is sourced from the [National Organization for Rare Disorders (NORD) database](https://rarediseases.org/), which compiles reports on rare diseases. 
+__NORD is committed to the identification, treatment, and cure of rare diseases through education, advocacy, research, and service programs.__
+The primary objective of developing ReCOP using the NORD database is to provide comprehensive expertise on rare diseases for LLMs. 
+This expertise can be leveraged to enhance the diagnostic capabilities of LLMs through retrieval-augmented generation.
+
+## Corpus Overview
+
+ReCOP divides each rare disease report into chunks: __overview, symptoms, causes, effects, related disorders, diagnosis__, and __standard therapies__. Each property of the disease corresponds to a specific chunk in ReCOP.
+In this manner, ReCOP generates 9268 chunks based on the reports of 1324 rare diseases for the NORD database, with each report producing seven chunks corresponding to the properties of a rare disease.
+
+<img width="800" height="290" src="https://anonymous.4open.science/r/redis-bench-EBE2/figures/corpus.png">
+
+## Using ReCOP for Retrieval Augmentation Generations
+
+Simply follow our benchmark repository [**ReDis-QA-Bench**](https://github.com/guanchuwang/redis-bench) to run the retrieval augmentation generations on the [ReDis-QA](https://huggingface.co/datasets/guan-wang/ReDis-QA) dataset:
+```bash
+git clone https://github.com/guanchuwang/redis-bench.git
+cd redis-bench
+bash rag-bench/scripts/run_exp.sh
+```
+
+
+## Benchmark Results of Retrieval Augmentation Generations
+
+Benchmark results of retrieval augmentation generations based on ReCOP, where the LLMs take [Llama-2-7B-chat](https://huggingface.co/meta-llama/Llama-2-7b-chat), [Mistral-7B-instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2), [Phi-3-7B-instruct](https://huggingface.co/microsoft/Phi-3-small-8k-instruct), [Gemmma-1.1-7B-it](https://huggingface.co/google/gemma-1.1-7b-it), and [Qwen-2-7B-Instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct).
+
+<img width="200" height="200" src="https://anonymous.4open.science/r/redis-bench-EBE2/figures/radar_Mistral-7B-v0.2.png">&nbsp;<img width="200" height="200" src="https://anonymous.4open.science/r/redis-bench-EBE2/figures/radar_Gemma-1.1-7B.png">&nbsp;<img width="200" height="200" src="https://anonymous.4open.science/r/redis-bench-EBE2/figures/radar_Phi-3-7B.png">&nbsp;<img width="200" height="200" src="https://anonymous.4open.science/r/redis-bench-EBE2/figures/radar_Qwen-2-7B.png">
+
+## Citation Information
+
+Coming soon
+
+

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