Update README.md

README.md

@@ -155,20 +155,8 @@ dataset_info:
     dtype: float32
   - name: openreview_submission_id
     dtype: string
-  splits:
-  - name: openreview_full_train
-    num_bytes: 1960055251
-    num_examples: 27710
-  - name: openreview_full_validation
-    num_bytes: 241413323
-    num_examples: 3463
-  - name: openreview_full_test
-    num_bytes: 236209810
-    num_examples: 3465
-  download_size: 1162696655
-  dataset_size: 2437678384
 configs:
-- config_name: acl_ocl
+- config_name: acl-ocl
   data_files:
   - split: train
     path: data/acl_ocl_train-*
@@ -216,7 +204,8 @@ Each sample is an academic paper for which either the citation count or the revi
 
 ## ACL-OCL Extended
 A dataset for citation count prediction only, based on the [ACL-OCL dataset](https://huggingface.co/datasets/WINGNUS/ACL-OCL/tree/main).
-Extended with updated citation counts, references and annotated research hypothesis
+Extended with updated citation counts, references and annotated research hypothesis.
+
 
 ## OpenReview (Last Update: 1.1.2025)
 A dataset for review score and citation count prediction, obtained by parsing OpenReview.
@@ -225,6 +214,7 @@ Due to licensing the dataset comes in different formats:
 ### Datasets without parsed pdfs of submissions (i.e. the fields introduction, background, methodology, experiments_results, conclusion, full_text are available)
 1. **openreview-public**: Contains full information on all OpenReview submissions that are accompanied with a CC BY 4.0 license.
 
+
 ### Datasets without parsed pdfs of submissions (i.e. the fields introduction, background, methodology, experiments_results, conclusion, full_text are None)
 1. **openreview-full**: Contains all OpenReview submissions, splits generated based on publications dates.  
 2. **openreview-iclr**: All ICLR submissions from the years 2018-2023 (training) and 2024 (validation and training).
@@ -232,6 +222,17 @@ Due to licensing the dataset comes in different formats:
 
 All datasets without parsed pdfs of submissions can be completed by running code available [here](https://github.com/NikeHop/automatic_scientific_quality_metrics)
 
+To load any of the datasets, replace `dataset_name` with the desired dataset and run:
+
+```python
+from datasets import load_dataset
+
+dataset_name = "openreview-full"
+dataset = load_dataset("nhop/scientific-quality-score-prediction", dataset_name)
+```
+
+
+
 ### Overview of Dataset columns
 
 | Attribute                | Type                                | Explanation                                                                 |