Update README.md

README.md

@@ -44,13 +44,15 @@ The dataset is available in two versions:
    - 2m: The complete unbalanced dataset with 1,912,024 clips.
  - test: The eval set with 18,886 clips.
 
-> **_NOTE:_** All versions of train sets share the same test set.
-
 ```bash
 # For the 20k version
 huggingface-cli download confit/audioset-16khz-wds --include 20k/train/*.tar  --repo-type=dataset --local-dir /path/to/store
 huggingface-cli download confit/audioset-16khz-wds --include 20k/test/*.tar  --repo-type=dataset --local-dir /path/to/store
 
+# For the 500k version
+huggingface-cli download confit/audioset-16khz-wds --include 500k/train/*.tar  --repo-type=dataset --local-dir /path/to/store
+huggingface-cli download confit/audioset-16khz-wds --include 500k/test/*.tar  --repo-type=dataset --local-dir /path/to/store
+
 # For the 2m version
 huggingface-cli download confit/audioset-16khz-wds --include 2m/train/*.tar  --repo-type=dataset --local-dir /path/to/store
 huggingface-cli download confit/audioset-16khz-wds --include 2m/test/*.tar  --repo-type=dataset --local-dir /path/to/store
@@ -73,11 +75,11 @@ Each `.tar` archive contains audio files and corresponding metadata.
 To load the dataset in Python using webdataset:
 
 ```python
-train_base_url = '/path/to/20k/train/shard-{i:05d}.tar'
-train_urls = [train_base_url.format(i=i) for i in range(7)]
+from glob import glob
+from datasets import load_dataset
 
-test_base_url = '/path/to/20k/test/shard-{i:05d}.tar'
-test_urls = [test_base_url.format(i=i) for i in range(6)]
+train_urls = glob('/path/to/20k/train/*.tar')
+test_urls = glob('/path/to/20k/test/*.tar')
 
 raw_datasets = load_dataset(
     "webdataset",