Update README.md

README.md

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+To accompany OpenPhenom, Recursion is releasing the **RxRx3-core** dataset, a challenge dataset in phenomics optimized for the research community. 
+RxRx3-core includes labeled images of 735 genetic knockouts and 1,674 small-molecule perturbations drawn from the [RxRx3 dataset](https://www.rxrx.ai/rxrx3), 
+image embeddings computed with [OpenPhenom](https://huggingface.co/recursionpharma/OpenPhenom), and associations between the included small molecules and genes. 
+
+Mapping the mechanisms by which drugs exert their actions is an important challenge in advancing the use of high-dimensional biological data like phenomics. 
+We are excited to release the first dataset of this scale probing concentration-response along with a benchmark and model to enable the research community to 
+rapidly advance this space.
+
+Loading the RxRx3-core image dataset
+```
+from datasets import load_dataset
+rxrx3_core = load_dataset("recursionpharma/rxrx3-core")
+```
+Loading OpenPhenom embeddings and metadata for RxRx3-core
+```
+from huggingface_hub import hf_hub_download
+import pandas as pd
+
+file_path_metadata = hf_hub_download("recursionpharma/rxrx3-core", filename="metadata_rxrx3_core.csv",repo_type="dataset")
+file_path_embs = hf_hub_download("recursionpharma/rxrx3-core", filename="OpenPhenom_rxrx3_core_embeddings.parquet",repo_type="dataset")
+
+open_phenom_embeddings = pd.read_parquet(file_path_embs)
+rxrx3_core_metadata = pd.read_csv(file_path_metadata)
+```
+Benchmarking code for this dataset is provided in the [EFAAR benchmarking repo](https://github.com/recursionpharma/EFAAR_benchmarking/tree/trunk).
+
 ---
 dataset_info:
   features: