Update README.md

README.md

@@ -54,7 +54,7 @@ from inference_tagger_standalone import Tagger
 
 tagger = Tagger(
     checkpoint_path="tagger_proto.safetensors",
-    vocab_path="tagger_vocab.json",
+    vocab_path="tagger_vocab_with_categories.json",
     device="cuda",
 )
 
@@ -71,7 +71,7 @@ tags = tagger.predict("https://example.com/image.jpg", threshold=0.35)
 # top-30 tags, pretty output
 python inference_tagger_standalone.py \
     --checkpoint tagger_proto.safetensors \
-    --vocab tagger_vocab.json \
+    --vocab tagger_vocab_with_categories.json \
     --images photo.jpg https://example.com/image.jpg \
     --topk 30
 
@@ -89,7 +89,7 @@ pip install fastapi uvicorn jinja2 aiofiles
 
 python tagger_ui_server.py \
     --checkpoint tagger_proto.safetensors \
-    --vocab tagger_vocab.json \
+    --vocab tagger_vocab_with_categories.json \
     --port 7860
 # → open http://localhost:7860
 ```
@@ -99,7 +99,7 @@ python tagger_ui_server.py \
 | File | Description |
 |---|---|
 | `*.safetensors` | Model weights (bfloat16) |
-| `tagger_vocab.json` | `{"idx2tag": [...]}` — 74 625 tag strings ordered by training frequency |
+| `tagger_vocab_with_categories.json` | `{"idx2tag": [...]}` — 74 625 tag strings ordered by training frequency |
 | `inference_tagger_standalone.py` | Self-contained inference script (no `transformers` dep) |
 | `tagger_ui_server.py` | FastAPI + Jinja2 web UI server |