Update README.md

README.md

@@ -32,6 +32,8 @@ size_categories:
 ## Title: GitHub Issues Dataset for Semantic Search
 ---
 
+The preview of the dataset was not available till the time I was uploading the dataset , but you can use it remotely via using the namespace/github-issues using load_dataset function , it's working fine.
+
 ## Dataset Summary
 
 This dataset was created following the last two sections of Chapter 5 from the Hugging Face NLP course. The course outlined steps to create a dataset for building a semantic search system using GitHub issues from the Hugging Face `datasets` repository. However, during the creation process, several challenges were encountered, including handling null values and timestamp-related errors. This dataset was refined by focusing on fields relevant to semantic search, such as `html_url`, `title`, `body`, `comments`, and `issue number`.
@@ -63,23 +65,19 @@ features: ['html_url', 'title', 'comments', 'body', 'number'],
 num_rows: 2893
 })
 
-
-
-
 ## Data Instances
 
 An example data instance looks like this:
 
-```json
 {
   "html_url": "https://github.com/huggingface/datasets/issues/7079",
   "title": "HfHubHTTPError: 500 Server Error: Internal Server Error for url:",
   "comments": ["same issue here. ... list of all comments csv"],
   "body": "### Describe the bug\n\nnewly uploaded datasets, since yesterday, yields an error.\r\n\r\n...body describing the issue",
   "number": 7079
-}
+} 
 
- Data Fields
+ ## Data Fields
  The dataset includes the following fields:
 
  html_url: URL of the GitHub issue (string).
@@ -89,18 +87,22 @@ An example data instance looks like this:
  number: GitHub issue number (int64).
 
 
-Source Data
+To use this data in an environment where transformers are installed , the data can be imported with 2 lines of code -
+
+from datasets import load_dataset
+
+ds = load_dataset("amannagrawall002/github-issues")
+
+
+## Source Data
 The dataset is crafted from scratch using the GitHub REST API, focusing on open issues from the Hugging Face datasets repository.
 
-Initial Data Collection and Normalization
+## Initial Data Collection and Normalization
 The creation of this dataset involved handling over 5000 issues, which exceeds the GitHub REST API's rate limit of 5000 requests per hour. Additionally, extracting comments required significant computational resources, highlighting the involvement of both automated processes and manual oversight.
 
-Considerations
+## Considerations
 This dataset is tailored for creating a semantic search application centered around GitHub issues. It does not contain data on pull requests, which may limit its applicability for tasks requiring such information.
 
-vbnet
-Copy code
-
 ### Additional Notes
 
 Anyone deeply engaged with the Hugging Face NLP course might attempt to create this dataset. While it's accessible remotely as described in the course, this specific version focuses solely on supporting semantic search applications. Other uses may require a dataset with broader field coverage.