Update README.md

README.md

@@ -69,48 +69,41 @@ All images are 96x96 pixels and are provided in PNG format.
 
 ## 🧼 Clean STL-10 Dataset, 🔧 How to Load?
 
-🎉 We uploaded our cleaned STL-10 dataset to Hugging Face! You can easily load and use it with the 🤗 `webdataset` library.
+🎉 We uploaded our cleaned STL-10 dataset to Hugging Face! You can easily load and use it with the 🤗 'datasets' or `webdataset` library.
 
----
+### 🥸 Load with datasets library (Recommended, Quick start)
+
+```python
+from datasets import load_dataset
+
+# Login using e.g. `huggingface-cli login` to access this dataset
+ds = load_dataset("Shu1L0n9/CleanSTL-10")
+```
 
 ### 🔧 Load with WebDataset
 
 ```python
-from huggingface_hub import hf_hub_url, HfFileSystem
 import webdataset as wds
+from huggingface_hub import HfFileSystem, get_token, hf_hub_url
 
-# Replace with your actual Hugging Face token
-token = "your_huggingface_token_here"
-fs = HfFileSystem(token=token)
+splits = {'train': 'train-*.tar', 'test': 'test-*.tar', 'unlabeled': 'unlabeled-*.tar'}
 
-repo_id = "Shu1L0n9/CleanSTL-10"
-splits = {
-    'train': '**/train-*.tar',
-    'test': '**/test-*.tar',
-    'unlabeled': '**/unlabeled-*.tar'
-}
+# Login using e.g. `huggingface-cli login` to access this dataset
+fs = HfFileSystem()
+files = [fs.resolve_path(path) for path in fs.glob("hf://datasets/Shu1L0n9/CleanSTL-10/" + splits["train"])]
+urls = [hf_hub_url(file.repo_id, file.path_in_repo, repo_type="dataset") for file in files]
+urls = f"pipe: curl -s -L -H 'Authorization:Bearer {get_token()}' {'::'.join(urls)}"
 
-def load_split(split):
-    pattern = f"hf://datasets/{repo_id}/{splits[split]}"
-    files = [fs.resolve_path(p) for p in fs.glob(pattern)]
-    urls = [hf_hub_url(f.repo_id, f.path_in_repo, repo_type="dataset") for f in files]
-    pipe_url = f"pipe: curl -s -L -H 'Authorization:Bearer {token}' {'::'.join(urls)}"
-    return wds.WebDataset(pipe_url, shardshuffle=False).decode("pil")
-
-# Load the splits
-train_ds = load_split("train")
-test_ds = load_split("test")
-unlabeled_ds = load_split("unlabeled")
+ds = wds.WebDataset(urls).decode()
 ```
 
-> ℹ️ Requires: `webdataset`, `huggingface_hub`, `fsspec`
+> ℹ️ Requires: `webdataset`, `huggingface_hub`
 > Install with:
 
 ```bash
-pip install webdataset huggingface_hub fsspec
+pip install webdataset huggingface_hub
 ```
 
-
 ### 🔑 How to Get Your Hugging Face Token
 
 To download from Hugging Face with authentication, you’ll need a **User Access Token**: