Fix typos

README.md

@@ -40,7 +40,7 @@ To construct Zyda-2, we took the best open-source datasets available: [Zyda](htt
 
 An early version of Zyda-2 was used as the primary dataset for phase 1 pretraining of our Zamba2 [series](https://huggingface.co/Zyphra/Zamba2-7B) [of](Zyphra/Zamba2-2.7B) [models](Zyphra/Zamba2-1.2B) which perform extremely strongly on a per-token basis and are often state-of-the-art for their size, testifying to the strength of Zyda-2 as a pretraining dataset.
 
-According to our evaluations, Zyda-2 is the most performant per-token open dataset available. Zyda-2 excels at educational and natural language reasoning content. For code performance, we reccomend mixing it with a pure code dataset such as [Starcoder](https://huggingface.co/bigcode/starcoder). 
+According to our evaluations, Zyda-2 is the most performant per-token open dataset available. Zyda-2 excels at educational and natural language reasoning content. For code performance, we recommend mixing it with a pure code dataset such as [Starcoder](https://huggingface.co/bigcode/starcoder). 
 
 
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@@ -51,11 +51,11 @@ According to our evaluations, Zyda-2 is the most performant per-token open datas
 For more information, please see our [technical blog](https://www.zyphra.com/post/building-zyda-2).
 
 ## How to download
-Since we preserved the schemas of original component datasets, attempting to dowlnoad the whole dataset using `datasets.load_dataset()` might fail during the stage of generating a split.
+Since we preserved the schemas of original component datasets, attempting to download the whole dataset using `datasets.load_dataset()` might fail during the stage of generating a split.
 
 To download the whole dataset we recommend to either clone the repository, or, if you must use the `datasets.load_dataset()`, download individual components separately.
 
-Example command to clone the repository using huggingface-cli: `huggingface-cli download Zyphra/Zyda-2--repo-type dataset`
+Example command to clone the repository using huggingface-cli: `huggingface-cli download Zyphra/Zyda-2 --repo-type dataset`
 
 Commands to download individual components:
  - DCLM:  `ds = datasets.load_dataset("Zyphra/Zyda-2", name="dclm_crossdeduped", split="train")`
@@ -71,11 +71,11 @@ We found the following optimal weights (in the sense of weights in the resultant
 
 | Component                    | Download size (parquet, GBs) | Documents (millions) | gpt-neox tokens (billions) |
 | --- | --- | --- | --- |
-| dclm-crossdeduped              |   8469.4                   |   2,590.5            |   3,348.942                |
+| dclm-crossdeduped              |   8,469.4                  |   2,590.5            |   3,348.942                |
 | zyda-crossdeduped-filtered     |   452.4                    |   247.7              |   163.6                    |
 | dolma_cc-crossdeduped-filtered |   668.2                    |   445.6              |   238.4                    |
-| fwe3                           |   3490.5                   |   1,279.1            |   1,319.2                  |
-| Total                          |   13080.5                  |   4,562.8            |   5,070.2                  |
+| fwe3                           |   3,490.5                  |   1,279.1            |   1,319.2                  |
+| Total                          |   13,080.5                 |   4,562.8            |   5,070.2                  |
 
 ### Dataset Description
 
@@ -90,9 +90,9 @@ We found the following optimal weights (in the sense of weights in the resultant
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 
-Each component has they're own individual schema. Please, consult with their respective sources for exact information.
+Each component has their own individual schema. Please, consult with their respective sources for exact information.
 
-However, in all components the document text is in `text` column, and unique document document id is in `nemo_id` column.
+However, in all components the document text is in the `text` column, and the unique document id is in the `nemo_id` column.
 
 Our Zyda-1 and Dolma-CC versions also have two additional columns corresponding to prediction of Nvidia's quality model (https://huggingface.co/nvidia/quality-classifier-deberta): `quality_prob` and `quality_pred`. 
 
@@ -114,7 +114,7 @@ FineWeb-Edu-score2: https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu-sc
 
 #### Personal and Sensitive Information
 
-As a language modelling dataset, it likely contains PII which has not been filtered out of the component datasets and which may have been missed by our own filters.
+As a language modeling dataset, it likely contains PII which has not been filtered out of the component datasets and which may have been missed by our own filters.
 
 ## Bias, Risks, and Limitations
 
@@ -139,3 +139,4 @@ If you use our dataset to train a model, please cite us at:
     day = {15}
 }
 ```
+