Upload README.md

README.md

@@ -1,23 +1,87 @@
 ---
-dataset_info:
-  features:
-  - name: sample_id
-    dtype: string
-  - name: sps
-    list: binary
-  - name: pps
-    list: binary
-  - name: idr
-    list: binary
-  splits:
-  - name: test
-    num_bytes: 5182319
-    num_examples: 1000
-  download_size: 5137755
-  dataset_size: 5182319
-configs:
-- config_name: default
-  data_files:
-  - split: test
-    path: data/test-*
+datasets:
+- name: leee99/yt8m-h264
+language:
+- en
+tags:
+- video
+- h264
+- bytestream
+- compressed-domain
+- youtube8m
+- machine-learning
+- dataset
+license: mit
+size_categories:
+- n<1K
+task_categories:
+- other
 ---
+
+
+# 📦 yt8m-h264
+
+`yt8m-h264` is a lightweight derivative of the YouTube-8M dataset that exposes **H.264 NAL units** (SPS, PPS, IDR) for efficient bytestream-level modeling and compression-aware video research.
+
+This dataset stores pre-processed **H.264 bytestream chunks** directly in **Arrow artifacts**, allowing fast loading with:
+
+```python
+from datasets import load_dataset
+ds = load_dataset("leee99/yt8m-h264")
+```
+
+No decoding, FFMPEG, or custom scripts are required at load time.
+
+---
+
+## ✅ What’s inside?
+
+* Extracted from YouTube-8M video segments
+* Each sample contains:
+
+  * **`sps`**: Sequence of SPS NAL units (as raw bytes)
+  * **`pps`**: Sequence of PPS NAL units (as raw bytes)
+  * **`idr`**: Sequence of IDR slice NAL units (as raw bytes)
+* Stored directly in Arrow (`binary`) columns
+
+A single example looks like:
+
+```python
+{
+    "sample_id": "00001234",
+    "sps": [b"\x00\x00\x00...\x67"],          # list of byte payloads
+    "pps": [b"\x00\x00\x00...\x68"],
+    "idr": [b"\x65\x88\x99..."],              # IDR slices as raw byte arrays
+}
+```
+
+These bytes correspond to Annex-B NAL units (`0x00 00 00 01 <nal-header> <payload>`), suitable for:
+
+* bytestream modeling
+* compressed-domain video understanding
+* tokenization (Byte-level / Bit-level)
+* entropy analysis
+* H.264 syntax learning
+
+---
+
+## ✅ Loading the dataset
+
+```python
+from datasets import load_dataset
+ds = load_dataset("leee99/yt8m-h264")
+
+print(ds)
+print(ds["test"][0])
+```
+
+Outputs:
+
+```
+DatasetDict({
+    test: Dataset({
+        features: ['sample_id', 'sps', 'pps', 'idr'],
+        num_rows: <N>
+    })
+})
+```