Update all files for BitDance-Tokenizer-diffusers

README.md

@@ -28,7 +28,37 @@ Each subfolder includes:
 - `config.json` with the autoencoder architecture
 - `conversion_metadata.json` documenting the source checkpoint and config
 
-## Quickstart (native diffusers)
+## Test (load tokenizer only)
+
+This repo is self-contained: it includes `bitdance_diffusers` (copied from BitDance-14B-64x-diffusers) for the `BitDanceAutoencoder` class. Run the test to verify loading and encode/decode:
+
+The test loads all three autoencoders and runs a quick encode/decode check with `ae_d16c32` (no full image generation).
+
+## Loading tokenizer autoencoders
+
+```python
+import sys
+from pathlib import Path
+
+# Self-contained: add local path so bitdance_diffusers is found
+BASE_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(BASE_DIR))
+
+from bitdance_diffusers import BitDanceAutoencoder
+
+# Load any tokenizer autoencoder (use repo path or local path)
+ae = BitDanceAutoencoder.from_pretrained(
+    "BiliSakura/BitDance-Tokenizer-diffusers",  # or str(BASE_DIR) for local
+    subfolder="ae_d16c32",
+)
+# ae_d16c32: z_channels=32, patch_size=16
+# ae_d32c128: z_channels=128, patch_size=32
+# ae_d32c256: z_channels=256, patch_size=32
+```
+
+## Using with a BitDance pipeline (full inference)
+
+To swap a tokenizer into a BitDance diffusers pipeline for image generation:
 
 ```python
 import torch