Update README.md

README.md

@@ -77,33 +77,37 @@ configs:
 This dataset is an instance of gsm8k dataset, converted to a simple html-like language that can be easily parsed (e.g. by BeautifulSoup). The data contains 3 types of tags:
 - gadget: A tag whose content is intended to be evaluated by calling an external tool (sympy-based calculator in this case)
 - output: An output of the external tool
-- result: The final answer of the mathematical problem (a number)
+- result: The final answer to the mathematical problem (a number)
 
 
 ## Supported Tasks
 
 The dataset is intended for training Chain-of-Thought reasoning **models able to use external tools** to enhance the factuality of their responses.
-This dataset presents in-context scenarios where models can out-source the computations in the reasoning chain to a calculator.
+This dataset presents in-context scenarios where models can outsource the computations in the reasoning chain to a calculator.
 
 
 ## Construction Process
 
-The answers in the original dataset was in in a structured but non-standard format. So, the answers were parsed, all arithmetical expressions
-were evaluated using a sympy-based calculator, the outputs were checked to be consistent with the intermediate results and finally exported
+The answers in the original dataset were in a structured but non-standard format. So, the answers were parsed, all arithmetical expressions
+were evaluated using a sympy-based calculator, the outputs were checked to be consistent with the intermediate results and exported
 into a simple html-like language that BeautifulSoup can parse.
 
 
 ## Content and Data splits
 
-Content corresponds to the original gsm8k dataset.
-
-In this version, we created validation set by sampling 200 random examples from the original train split. The original data splits can be downloaded using:
+For convenience, we created a validation set by sampling 200 random examples from the original train split. You can load this using:
 
+```python3
+datasets.load_dataset("MU-NLPC/Calc-gsm8k")
 ```
+
+The original data splits can be loaded using:
+
+```python3
 datasets.load_dataset("MU-NLPC/Calc-gsm8k", "original-splits")
 ```
 
-See [gsm8k HF dataset](https://huggingface.co/datasets/gsm8k) and [official repository](https://github.com/openai/grade-school-math) for more info.
+For more info about the content of the dataset, see [gsm8k HF dataset](https://huggingface.co/datasets/gsm8k) and the [official repository](https://github.com/openai/grade-school-math).
 
 
 ## Licence
@@ -113,7 +117,7 @@ MIT, consistently with the original dataset.
 
 ## Cite
 
-If you use this version of dataset in research, please cite the [original GSM8K paper](https://arxiv.org/abs/2110.14168) and [Calc-X collection](https://arxiv.org/abs/2305.15017) as follows:
+If you use this version of the dataset in research, please cite the [original GSM8K paper](https://arxiv.org/abs/2110.14168), and [Calc-X collection](https://arxiv.org/abs/2305.15017) as follows:
 
 ```bibtex
 @inproceedings{kadlcik-etal-2023-soft,